MLI Publications

MLI Publications

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2023

P 23-1
Alemi, F., Guralnik, E., Vang, J., Wojtusiak, J., Peterson, R., Roess, A. and Jain, P., "Guidelines for Triage of COVID-19 Patients Presenting With Multisystemic Symptoms," Quality Management in Healthcare, 32 (Supplement 1), S3-S10, 2023.

P 23-2
Alemi, F., Vang, J., Bagais, W.H., Guralnik, E., Wojtusiak, J., Moeller, FG, Schilling, J, Peterson, R., Roess, A. and Jain, P., "Combined Symptom Screening and At-Home Tests for COVID-19," Quality Management in Healthcare, 32 (Supplement 1), S11-S20, 2023.

P 23-3
Wojtusiak, J., Bagais, W.H., Vang, J., Guralnik, E., Roess, A. and Alemi, F., "The role of symptom clusters in triage of COVID-19 patients," Quality Management in Healthcare, 32 (Supplement 1), S21-S28, 2023.

P 23-4
Wojtusiak, J., Bagais, W.H., Vang, J., Roess, A. and Alemi, F., "Order of Occurrence of COVID-19 Symptoms," Quality Management in Healthcare, 32 (Supplement 1), S29-S34, 2023.

P 23-5
Min, H., Mobahi, H. and Wojtusiak, J., "Application of Synthetic Datasets across Courses in Health Informatics Education," International Conference on Healthcare Informatics (ICHI), Houston, Texas, 2023.

P 23-6
Haghighathoseini, A., Vinnakota, S.S., Thomas, R.J., Frankenfeld, C.L., Leslie, T.F., Min, H., Menon, N.M. and Wojtusiak, J., "Arbitrary Choices Matter: A Case of Cohort Selection in N3C," Poster Presentation at American Medical Informatics Annual Symposium, November, 2023.

P 23-7
Alsadah, G., Wojtusiak, J., Anand, P., Dague, L. and Wagner, K., "Who Gets Health Benefits? An (Un)biased Machine Learning Prediction," Poster Presentation at American Medical Informatics Annual Symposium, November 2023.

P 23-8
Shih, H., Durbha, S. and Wojtusiak, J., "Disparities in Hospital Readmissions and Lack of Fairness," Poster Presentation at American Medical Informatics Annual Symposium, November, 2023.

P 23-9
Ngana, LP and Wojtusiak, J., "External Validation of Computational Barthel Index: Why Accuracy Drops?," enefits? An (Un)biased Machine Learning Prediction,, November 2023.

2022

P 22-1
Pierobon, M., Robert, NJ., Northfelt, DW., Jahanzeb, M., Wong, S., Hodge, KA., Baldelli, E., Aldrich, J., Craig, DW., Liotta, LA., Avramovic, S., Wojtusiak, J., Alemi, F., Wulfkuhle, JD., Bellos, A., Gallagher, RI., Arguello, D., Conrad, A., Kemkes, A., Loesch, DM., Vocila, L., Dunetz, B., Carpten, JD., Petricoin, E. and Anthony, SP., "Multi‐omic molecular profiling guides efficacious treatment selection in refractory metastatic breast cancer: a prospective phase II clinical trial," Molecular Oncology, 16(1), Jan. 2022.

P 22-2
Bagais, W.H. and Wojtusiak, J., "Dashboard for Machine Learning Models in Health Care," HEALTHINF 2022, 5, 484-492, 2022.

P 22-3
Wang, Y., Tran, P. and Wojtusiak, J., "From Wearable Device to OpenEMR: 5G Edge Centered Telemedicine and Decision Support System," HEALTHINF 2022, 5, 493-500, 2022.

P 22-4
Wojtusiak, J. and Asadzadehzanjani, N., "Discussion on Comparing Machine Learning Models for Health Outcome Prediction," HEALTHINF 2022, 5, 713-720, 2022.

P 22-5
Asadzadehzanjani, N., "A Study of Administrative Data Representation for Machine Learning," PhD Dissertation, Health Informatics Program, George Mason University, 2022.

P 22-6
Wojtusiak, J., Alsadah, G., Anand, P., Dague, L. and Wagner, K., "Access to Paid Leave Among Those with Caregiving Needs," Abstract in 2022 APPAM Fall Research Conference, 2022.

2021

P 21-1
Wojtusiak, J., Alemi, F., Asadzadehzanjani, N., Levy, C. and Williams, A., "Computational Barthel Index: an automated tool for assessing and predicting activities of daily living among nursing home patients," BMC Medical Informatics and Decision Making, 21, 2021.

P 21-2
Wojtusiak, J., Bagchi, P., Durbha, S., Mobahi, H., Mogharab Nia, R. and Roess, A., "COVID-19 Symptom Monitoring and Social Distancing in a University Population," Journal of Health Informatics Research, 2021.

P 21-3
Wojtusiak, J., Asadzadehzanjani, N., Levy, C., Alemi, F. and Williams, A., "Online Decision Support Tool that Explains Temporal Prediction of Activities of Daily Living (ADL)," HEALTHINF, 2021.

P 21-4
Wojtusiak, J., "Reproducibility, Transparency and Evaluation of Machine Learning in Health Applications," HEALTHINF, 2021.

P 21-5
Wojtusiak, J., Vakkalagadda, V., Wang, Y., Durbha, S., Alemi, F. and Roess, A., "Towards Wi-Fi Contact Prediction: Methods and Initial Results," Reports of the Machine Learning and Inference Laboratory, MLI 21-1, 2021.

P 21-6
Wojtusiak, J., Wang, Y., Vakkalagadda, V., Alemi, F. and Roess, A., "Using Wi-Fi Infrastructure to Predict Contacts During Pandemics," IEEE International Conference on Healthcare Informatics, Victoria, Canada, 2021.

P 21-7
Bagais, W.H., "Dashboard for Machine Learning Models in Health Care," MS Thesis, Health Informatics Program, George Mason University, 2021.

P 21-8
Asadzadehzanjani, N. and Wojtusiak, J., "Administrative Health Data Representation for Mortality and High Utilization Prediction," VLDB Data Management and Analytics for Medicine and Healthcare Workshop, 2021.

P 21-9
Cheng, X,, Lin, SY., Wang, K., Hong, YA., Wojtusiak, J., Gress, D., Cheskin, L.J. and Xue, H., "Healthfulness Assessment of Recipes Shared on Pinterest: Natural Language Processing and Content Analysis," Journal of Medical Internet Research, 23, 4, e25757, 2021.

P 21-10
Guralnik, E., Alemi, F., Vang, J., Wojtusiak, J., Wilson, A. and Roess, A., "Modeling the Probability of COVID-19 Vs. Influenza or Influenza-like-Illnesses (ILI) Based on Symptom Screening," 2021 AcademyHealth Annual Research Meeting, 2021.

P 21-11
Alemi, Y., Min, H., Yousefi, M., Becker L.K., Hane C.A., Nori V.S. and Wojtusiak, J., "Effectiveness of common antidepressants: a post market release study," eClinicalMedicine, 41, November 2021.

2020

P 20-1
Wojtusiak, J., "Machine Learning and Inference Reporting Criteria," Reports of the Machine Learning and Inference Laboratory, MLI 20-1, 2020.

P 20-2
Zare, M., "Intelligent Patient Data Generator," Ph.D. Dissertation, Health Services Research, Knowledge Discovery and Health Informatics, George Mason University, 2020.

P 20-3
Wang, Y. and Wojtusiak, J., "Towards Active Learning for User-defined Chest X-Ray Diagnosis System," Reports of the Machine Learning and Inference Laboratory, MLI 20-2, 2020.

P 20-4
Wojtusiak, J., Bagchi, P., Durbha, S., Mobahi, H., Mogharab Nia, R. and Roess, A., "COVID-19 Symptom Monitoring and Social Distancing in a University Population," IEEE International Conference on Healthcare Informatics (ICHI), November, 2020.

P 20-5
Mogharab Nia, R. and Wojtusiak, J., "Using Landmark Information to Enhance Location Prediction for Missing People with Alzheimer’s Disease," Poster Presentation at American Medical Informatics Annual Symposium, November. 2020.

P 20-6
Wojtusiak, J., Bagchi, P., B. Durai, U. N., Koester, R. J., Middle, B. , Mogharab Nia, R. and Tompkins, C., "Analysis of Wandering Patterns of Individuals with Alzheimers Disease," Reports of the Machine Learning and Inference Laboratory, MLI 20-3, 2020.

2019

P 19-1
Wojtusiak, J. and Mogharab Nia, R., "Location Prediction Using GPS Trackers: Can Machine Learning Help Locate the Missing People with Dementia?," Internet of Things, Elsevier, 2019 (in press).

P 19-2
Kheirbek, R., Alemi, Y., Wojtusiak, J., Kheirbek, L., Madison, S., Fokar, A., Doukky, R. and Moore, H.J., "Impact of Hospice and Palliative Care Service Utilization on All-Cause 30-Day Readmission Rate for Older Adults Hospitalized with Heart Failure," American Journal of Hospice and Palliative Medicine, 2019.

P 19-3
Mobahi, H., Asadzadehzanjani, N. and Wojtusiak, J., "Data-driven Categorization of Opioid Abuse Trajectories," Poster at AMIA Informatics Summit, San Francisco, CA, March, 2019.

P 19-4
Asadzadehzanjani, N., Wojtusiak, J., Williams, A. and Levy, C., "Generic vs. Specialized Models for Assessing Disabilities among People with Dementia," Poster at AMIA Annual Symposium, Washington D.C., November, 2019.

P 19-5
Mobahi, H., Min, H. and Wojtusiak, J., "Synthetic Data for Teaching Data Integration in Informatics Graduate Program," Poster at AMIA Annual Symposium, Washington D.C., November, 2019.

P 19-6
Wojtusiak, J., B. Durai, U. N., Koester, R. J., Middle, B. , Mogharab Nia, R. and Tompkins, C., "Using GPS to Locate the Missing and Track Wandering in People with Alzheimer’s Disease," AMIA, 2019.

P 19-7
Wojtusiak, J. and Park, J., "Understanding interdependencies in technical content: from media to curriculum mapping in health informatics," Presentation at OLC Accelerate, Orlando, FL, 2019.

2018

P 18-1
Wojtusiak, J. and Mogharab Nia, R., "Location Prediction Using GPS Trackers: Towards Predicting Wandering in People with Dementia," Reports of the Machine Learning and Inference Laboratory, MLI 18-1, 2018.

P 18-2
Avramovic, S., Asadzadehzanjani, N., Mogharab Nia, R., Baldelli, E., Petricoin, E., Pierobon, M. and Wojtusiak, J., "The Side Out Foundation Metastatic Breast Cancer Database, an Open-access Portal for multi-omics Molecular Data and More," Reports of the Machine Learning and Inference Laboratory, MLI 18-2, 2018.

P 18-3
Zare, M., Wojtusiak, J. and Nilashi, M., "Prediction of Patients’ Mortality during Hospitalizations," Journal of Soft Computing and Decision Support Systems, 5(4), 26-32, 2018.

P 18-4
Wojtusiak, J., Elashkar, E. and Mogharab Nia, R., "C-LACE2: computational risk assessment tool for 30-day post hospital discharge mortality," Health and Technology, Springer, In Press Online 2018.

P 18-5
Zare, M., Narayan, M., Lasway, A., Kitsantas, P., Wojtusiak, J. and Oetjen, C.A., "Influence of Adverse Childhood Experiences on Anxiety and Depression In Children Aged 6 to 11 Years," Continuing Nursing Education, 44(6), 267-274, 2018.

P 18-6
Zare, M. and Wojtusiak, J., "Weighted Itemsets Error (WIE) Approach for Evaluating Generated Synthetic Patient Data," 2018 17th IEEE International Conference on Machine Learning and Applications, 2018.

P 18-7
ElRafey, A. and Wojtusiak, J., "A Hybrid Active Learning and Progressive Sampling Algorithm," International Journal of Machine Learning and Computing, 8(5), 423-427, 2018.

P 18-8
Wojtusiak, J., Min, H., Elashkar, E. and Mobahi, H., "Guiding Supervised Learning by Bio-Ontologies in Medical Data Analysis," Artificial Intelligence for Knowledge Management. AI4KM, 518, Springer, 2018.

2017

P 17-1
ElRafey, A. and Wojtusiak, J., "Recent advances in scaling‐down sampling methods in machine learning," Wiley Interdisciplinary Reviews: Computational Statistics, 2017.

P 17-2
Min, H., Avramovic, S., Wojtusiak, J., Khosla, R., Fletcher, RD., Alemi, F. and Elfadel Kheirbek, R., "A Comprehensive Multimorbidity Index for Predicting Mortality in Intensive Care Unit Patients," Journal of palliative medicine, 20(1), 35-41, 2017.

P 17-3
Min, H., Mobahi, H., Irvin, K., Avramovic, S. and Wojtusiak, J., "Predicting activities of daily living for cancer patients using an ontology-guided machine learning methodology," Journal of Biomedical Semantics, 8(1), 39, 2017.

P 17-4
Wojtusiak, J., Elashkar, E. and Mogharab Nia, R., "C-LACE: Computational Model to Predict 30-Day Post-Hospitalization Mortality," HealthInf, 2017.

P 17-5
Mogharab Nia, R., Helmchen, L. and Wojtusiak, J., "Using Exact Patient Mobility Data to Predict Wandering Behavior," Presentation at 8th Conference on Health IT and Analytics (CHITA), Washington D.C., November, 2017.

2016

P 16-1
Wojtusiak, J., Levy, C., Williams, A. and Alemi, F., "Predicting Functional Decline and Recovery following Hospitalization of Residents in Veterans Affairs Nursing Homes," The Gerontologist, 56(1), 2016.

P 16-2
Levy, C., Zargoush, Manaf, Williams, A., Williams, A.R., Wojtusiak, J., Kheirbek, R., Giang, P. and Alemi, F., "Sequence of Functional Loss and Recovery in Nursing Homes," The Gerontologist, 56(1), 2016.

P 16-3
Min, H., Mobahi, H., Vukomanovic, S., Irvin, K., Krasniqi, I., Avramovic, S. and Wojtusiak, J., "Applying an Ontology-guided Machine Learning Methodology to SEER-MHOS Dataset," , Orlando,FL, Bio-Ontologies SIG, 2016.

P 16-4
Kheirbek, R., Wojtusiak, J., Alemi, F. and Vlaicu, S., "Lack of Evidence for Racial Disparity in 30-Day All-Cause Readmission Rate for Older US Veterans Hospitalized with Heart Failure," Quality Management in Health Care, 25(4), 191–196, 2016.

P 16-5
Wojtusiak, J., Elashkar, E. and Mogharab Nia, R., "Integrating Complex Health Data for Analytics," Reports of The Machine Learning and Inference Laboratory, MLI-16-1, 2016.

P 16-6
Aloudah, F.M. and Wojtusiak, J., "Towards Automated Selection of Patient-Specific Education Materials in Ambulatory Care Settings," Poster at American Medical Informatics Association Annual Symposium, November, 2016.

P 16-7
Min, H., Oz, T., Vukomanovic, S., Mobahi, H., Irvin, K., Krasniqi, I. and Wojtusiak, J., "Applying Machine Learning Methods to Predict Activities of Daily Living for Cancer Patients," Poster at American Medical Informatics Association Annual Symposium, November, 2016.

P 16-8
Min, H., Oz, T., Vukomanovic, S., Mobahi, H., Irvin, K., Krasniqi, I. and Wojtusiak, J., "Visualizing the Effects of Cancers on Relationships Between Comorbidities and Activities of Daily Living," Poster at American Medical Informatics Association Annual Symposium, November, 2016.

P 16-9
Wojtusiak, J., "Towards Intelligent Patient Data Generator," Reports of the Machine Learning and Inference Laboratory, MLI 16-2, 2016.

2015

P 15-1
Levy, C., Kheirbek, R., Alemi, F., Wojtusiak, J., Sutton, B., Williams, A.R. and Williams, A., "Predictors of six-month mortality among nursing home residents: diagnoses may be more predictive than functional disability," Journal of Palliative Medicine, 18(2), 100-6, 2015.

P 15-2
Madison, S. and Wojtusiak, J., "Engaging Students in Health Informatics Research: Strategies for Success," Presentation at HIMSS 2015 Annual Conference, AUPHA academic forum, Chicago, IL, 2015.

P 15-3
Helmchen, L., Burke, ME and Wojtusiak, J., "Designing highly reliable adverse-event detection systems to predict subsequent claims," Journal of Healthcare Risk Management, 34(4), 7-17, 2015.

P 15-4
Ngufor, C., Wojtusiak, J. and Pathak, J., "A Systematic Prediction of Adverse Drug Reactions Using Pre-clinical Drug Characteristics and Spontaneous Reports," International Conference on Healthcare Informatics (ICHI), Dallas, TX, USA, 21-23 Oct. 2015.

2014

P 14-1
Ngufor, C. and Wojtusiak, J., "Learning from Large Distributed Data: A Scaling Down Sampling Scheme for Efficient Data Processing," International Journal of Machine Learning and Computing (IJMLC), Vol.4(3), 216-224, 2014.

P 14-2
Ngufor, C., Wojtusiak, J., Hooker, A., Oz, T. and Hadley, J., "Extreme Logistic Regression: A Large Scale Learning Algorithm with Application to Prostate Cancer Mortality Prediction," Proceedings of the The 27th International Florida Artificial Intelligence Research Society Conference, 2014.

P 14-3
Ngufor, C. and Wojtusiak, J., "Extreme logistic regression," Advances in Data Analysis and Classification (ADAC), Springer, 2014.

P 14-4
Oz, T. and Wojtusiak, J., "Specialty and Physician Referral Network," International Sunbelt Social Network Conference XXXIV (INSNA), St. Pete Beach, FL, Feb 2014.

P 14-5
Oz, T. and Wojtusiak, J., "Turkish News Audience and Their Political Leanings on Twitter," 7th Political Networks Conference (PolNet), Montreal, QC, Canada , May 2014.

P 14-6
Wojtusiak, J., Ngufor, C., Helmchen, L. and Hadley, J., "Creating Clinically Homogeneous Groups of Prostate Cancer Patients," Proceedings of AMIA 2014 Annual Symposium, Washington D.C., 2014.

P 14-7
Wojtusiak, J., "Rule Learning in Healthcare and Health Services Research," Dua S., Acharya U., Dua P. (eds) Machine Learning in Healthcare Informatics, Berlin, Heidelberg, Springer, 2014.

2013

P 13-1
Domanski, P. A., McLinden, M.O., Brown, J.S., Heo, J. and Wojtusiak, J., "A THERMODYNAMIC ANALYSIS OF REFRIGERANTS: PerFormance limits OF the vapor compression cycle," International Journal of Refrigeration

P 13-2
Wojtusiak, J. and Kolaceveki, A., "Machine Learning-based Detection of Health Data Elements," American Medical Informatics Annual Symposium, Washington D.C, Nov 2013.

P 13-3
Oz, T., Ngufor, C. and Wojtusiak, J., "Mining Progress Notes for Prediction of Activities of Daily Living," American Medical Informatics Annual Symposium, Washington D.C, Nov 2013.

P 13-4
Ngufor, C. and Wojtusiak, J., "Learning from Large-Scale Distributed Health Data: An Approximate Logistic Regression Approach," International Conference on Machine Learning, Workshop on Role of Machine Learning in Transforming Healthcare, 2013.

P 13-5
Ngufor, C. and Wojtusiak, J., "Unsupervised Labeling of Data for Supervised Learning and Its Application to Medical Claims Prediction," Computer Science Journal, 14, 2, 191-214, AGH Press, 2013.

2012

P 12-1
Wojtusiak, J., "AQ Learning," Encyclopedia of the Sciences of Learning, Springer, 2012.

P 12-2
Wojtusiak, J., "Machine Learning," Encyclopedia of the Sciences of Learning, Seel, N.M. (Ed.), Springer, 2012.

P 12-3
Wojtusiak, J., "Rule Learning," Encyclopedia of the Sciences of Learning, Seel, N.M. (Ed.), Springer, 2012.

P 12-4
Michalski, R. S. and Wojtusiak, J., "Reasoning with Missing, Not-applicable and Irrelevant Meta-values in Concept Learning and Pattern Discovery," Journal of Intelligent Information Systems, 39,1, 141-166, Springer, 2012.

P 12-5
Warden, T. and Wojtusiak, J., "Intelligent Modeling and Control for Autonomous Logistics," In Advances in Intelligent Modelling and Simulation: Artificial Intelligence-based Models and Techniques in Scalable Computing, Kołodziej, J., Khan, S.U. and Burczynski, T. (Eds.), 295-325, Springer, 2012.

P 12-6
Yashar, D., Wojtusiak, J., Kaufman, K. and Domanski, P. A., "A Dual Mode Evolutionary Algorithm for Designing Optimized Refrigerant Circuitries for Finned-Tube Heat Exchangers," HVAC&R Research, 18,5, 834-844, Taylor & Francis, 2012.

P 12-7
Wojtusiak, J., Warden, T. and Herzog, O., "The Learnable Evolution Model in Agent-based Delivery Optimization," Memetic Computing, 4, 3, 165-181, 2012.

P 12-8
Irvin, K., Ngufor, C. and Wojtusiak, J., "Comparison of Classification Learning Methods for Medical Claims Payments," American Medical Informatics Annual Symposium, Chicago, November, 2012.

P 12-9
Wojtusiak, J., "Recent Advances in AQ21 Rule Learning System for Healthcare Data," American Medical Informatics Annual Symposium, Chicago, November, 2012.

P 12-10
Wojtusiak, J., Warden, T. and Herzog, O., "Machine Learning in Agent-based Stochastic Simulation: Inferential Theory and Evaluation in Transportation Logistics," Computers & Mathematics with Applications, 64, 12, 3658-3665, 2012.

P 12-11
Wojtusiak, J., "Semantic Data Types in Machine Learning from Healthcare Data," International Conference on Machine Learning and Applications (ICMLA), Florida, December, 2012.

2011

P 11-1
Wojtusiak, J., Shiver, J., Ngufor, C. and Ewald, R., "Machine Learning in Hospital Billing Management," Presentation at HIMSS 2011 Acedemic Forum (Hosted by AUPHA), Orlando, FL, February 20, 2011.

P 11-2
Wojtusiak, J., Warden, T. and Herzog, O., "Agent-based Pickup and Delivery Planning: The Learnable Evolution Model Approach," Proceedings of The Fifth International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS-2011), Seoul, Korea, June 30 - July 2, 2011.

P 11-3
Wojtusiak, J. and Baranova, A. V., "Model Learning from Published Aggregated Data," Learning Structure and Schemas from Documents, Studies in Computational Intelligence, 375, 369-384, 2011.

P 11-4
Wojtusiak, J., Ngufor, C., Ewald, R. and Shiver, J., "Rule-based Prediction of Medical Claims’ Payments: A Method and Initial Application to Medicaid Data," Proceedings of the International Conference on Machine Learning and Applications (ICMLA), Honolulu, HI, 2011.

P 11-5
Baranova, A. V., Wojtusiak, J., Irvin, K. and Birerdinc, A., "Using Published Medical Results and Non-homogenous Data in Rule Learning," Proceedings of the International Conference on Machine Learning and Applications (ICMLA), Honolulu, HI, 2011.

P 11-6
Wojtusiak, J., Gewa, C.A. and Pawloski, LR.., "Dietary Assessment in Africs: Integration with Innovative Technology," African Journal of Food, Agriculture, Nutrition, and Development, 11-7-2011.

2010

P 10-1
Wojtusiak, J. and Kaufman, K., "Ryszard S. Michalski: The Vision and Evolution of Machine Learning," Advances in Machine Learning I, 3-22, Springer, 2010.

P 10-2
Wojtusiak, J., Prior, S. and Thompson, D., "Adaptive Infrastructure Protection: Machine Learning Approach to Data Collection," Workshop on Grand Challenges in Modeling, Simulation, and Analysis for Homeland Security (MSAHS-2010), March 17-18, 2010, Arlington, VA.

P 10-3
Yashar, D., Domanski, P. A., Wojtusiak, J. and Kaufman, K., "Evolutionary Computation Approach to Heat Exchanger Optimization," Proceedings of the American Society of Heating, Refrigerating and Air-Conditioning Engineers Annual Conference, Albuquerque, NM, June 26-30, 2010.

P 10-4
Warden, T. and Wojtusiak, J., "Learnable Evolutionary Optimization in Autonomous Pickup & Delivery Planning: A Scenario, System Architecture and Initial Results," TZI-Bericht Nr. 55, TZI, Universität Bremen, 2010.

P 10-5
Wojtusiak, J. and Zurada, J. M., "Automated Computational Intelligence and Machine Learning Advising in Healthcare," Proceedings of the AMIA 2010 Annual Symposium, Washington D.C, 2010.

P 10-6
Sniezynski, B., Wojcik, W., Gehrke J. D. and Wojtusiak, J., "Combining Rule Induction and Reinforcement Learning: An Agent-based Vehicle Routing," Proceedings of the Ninth International Conference on Machine Learning and Applications (ICMLA 2010), Washington D.C, pp. 851-856, 12-14 Dec. 2010.

P 10-7
Wojtusiak, J. and Herzog, O., "Distributed Decision Support in Disruptive Environments," Reports of the Machine Learning and Inference Laboratory, MLI 10-1, December 2010.

P 10-8
Wojtusiak, J. and Alemi, F., "Analyzing Decisions Using Datasets with Multiple Attributes: A Machine Learning Approach," Handbook of Healthcare Delivery Systems, CRC Press, 2010.

P 10-9
Baranova, A. V., Wojtusiak, J., Stepanova, M., Simanivanh, T., Fang, Y., Chandhoke, V. and Younossi, Z.M., "Validation of the Machine Learning Algorithm to Diagnose Non-alcoholic Fatty Liver Disease (NAFLD) and Non-alcoholic Steatohepatitis (NASH)," Digestive Disease Week, New Orleans, LA, May 1-5, 2010.

2009

P 09-1
Zurada, J. M., Mazurowski, M.A., Abdullin, A., Ragade, R., Wojtusiak, J. and Gentle, J. E., "Building Virtual Community in Computational Intelligence and Machine Learning," Computational Intelligence Magazine, 4, 1, 43-54, 2009.

P 09-2
Wojtusiak, J., "The LEM3 System for Multitype Evolutionary Optimization," Computing and Informatics, 28, 225-236, 2009.

P 09-3
Mehta, D., Perchansky, K., Wojtusiak, J., Moidu, K. and He, Z., "Microaspiration from Gastroesophageal Reflux Is Common in Children with Asthma," Poster at Pediatric Academic Societies Annual Meeting, Baltimore, MD, May 2-5, 2009.

P 09-4
Wojtusiak, J., Zurada, J. M., Malof, J.M., Mehta, D. and Moidu, K., "Toward VO-based Collaboration between Computational Intelligence - Machine Learning and Healthcare Communities," Recent Advances in Intelligent Information Systems, Klopotek, M.A., Przepiorkowski, A, Wierzchon, S.T. and Trojanowski, K. (Eds.), 507-518, Academic Publishing House EXIT

P 09-5
Wojtusiak, J., Michalski, R. S., Simanivanh, T. and Baranova, A. V., "Towards application of rule learning to the meta-analysis of clinical data: An example of the metabolic syndrome," International Journal of Medical Informatics, 78, 12, e104-e111, 2009.

P 09-6
Wojtusiak, J., Chorowski, J., Pietrzykowski, J. and Zurada, J. M., "Searching and Reasoning with Distributed Resources in Computational Intelligence and Machine Learning," Journal of Applied Computer Science Methods, 1,2, 2009.

P 09-7
Landon, B.E. , Reschovsky, J.D. , Pham, H.H., Kitsantas, P., Wojtusiak, J. and Hadley, J., "Creating a parsimonious typology of physician financial incentives," Health Services and Outcomes Research Methodology, 9, 219–233, 2009.

2008

P 08-1
Michalski, R. S. and Wojtusiak, J., "Analyzing Diaries for Analytical Relapse Prevention Using Natural Induction: A Method and Preliminary Results," Quality Management in Health Care, 17, 80-89, 2008.

P 08-2
Zurada, J. M., Wojtusiak, J., Gentle, J. E., Chowdhury, F., Ragade, R. and Jeannot, C., "Computational Intelligence and Machine Learning Virtual Infrastructure Network (CIMLVIN)," Poster at the National Science Foundation Workshop on Building Effective Virtual Organizations, Washington D.C, January 14-16, 2008.

P 08-3
Gehrke J. D. and Wojtusiak, J., "A Natural Induction Approach to Traffic Prediction for Autonomous Agent-based Vehicle Route Planning," Reports of the Machine Learning and Inference Laboratory, MLI 08-1, George Mason University, VA, February 17, 2008.

P 08-4
Michalski, R. S. and Wojtusiak, J., "The Distribution Approximation Approach to Learning from Aggregated Data," Reports of the Machine Learning and Inference Laboratory, MLI 08-2, 2008.

P 08-5
Zurada, J. M., Wojtusiak, J., Chowdhury, F., Gentle, J. E., Mazurowski, M.A. and Jeannot, C., "Computational Intelligence Virtual Community: Framework and Implementation Issues," Proceedings of the IEEE World Congress on Computational Intelligence, Hong Kong, June 1-6, 2008.

P 08-6
Pietrzykowski, J. and Wojtusiak, J., "Learning Attributional Ruletrees," Proceedings of the 16th International Conference Intelligent Information Systems, Zakopane, Poland, June 16-18, 2008.

P 08-7
Wojtusiak, J., "Data-driven Constructive Induction in the Learnable Evolution Model," Proceedings of the 16th International Conference Intelligent Information Systems, Zakopane, Poland, June 16-18, 2008.

P 08-8
Gehrke J. D. and Wojtusiak, J., "Traffic Prediction for Agent Route Planning," Proceedings of the International Conference on Computational Science, Lecture Notes in Computer Science, Krakow, Poland, Springer, 2008.

P 08-9
Mazurowski, M.A., Zurada, J. M., Wojtusiak, J., Ragade, R., Gentle, J. E. and Abdullin, A., "Workshop on Building Computational Intelligence and Machine Learning Virtual Organizations," , George Mason University, VA, October 28, 2008.

P 08-10
Zurada, J. M., Wojtusiak, J., Mazurowski, M.A., Mehta, D., Moidu, K. and Margolis, S., "Toward Multidisciplinary Collaboration in the CIML Virtual Community," Workshop on Building Computational Intelligence and Machine Learning Virtual Organizations, George Mason University, VA, pp. 62-66, October 28, 2008.

P 08-11
Boyle, C., Abdullin, A., Ragade, R., Mazurowski, M.A., Wojtusiak, J. and Zurada, J. M., "Workflow considerations in the emerging CI-ML virtual organization," Workshop on Building Computational Intelligence and Machine Learning Virtual Organizations, George Mason University, VA, pp 67-70, October 28, 2008.

P 08-12
Pietrzykowski, J., "Demonstration and Application of Rule Discovery Methods Using iAQ," Workshop on Building Computational Intelligence and Machine Learning Virtual Organizations, George Mason University, VA, pp 39-44, October 24, 2008.

2007

P 07-1
Michalski, R. S. and Wojtusiak, J., "Semantic and Syntactic Attribute Types in AQ Learning," Reports of the Machine Learning and Inference Laboratory, MLI 07-1, George Mason University, Fairfax, VA, 2007.

P 07-2
Michalski, R. S., Wojtusiak, J. and Kaufman, K., "Progress Report on the Learnable Evolution Model," Reports of the Machine Learning and Inference Laboratory, MLI 07-2, George Mason University, Fairfax, VA, 2007.

P 07-3
Michalski, R. S. and Wojtusiak, J., "Generalizing Data in Natural Language," Proceedings of the International Conference Rough Sets and Emerging Intelligent Systems Paradigms, RSEISP 07, Lecture Notes in Computer Science, Springer, 2007.

P 07-4
Michalski, R. S. and Pietrzykowski, J., "iAQ: A program that discovers rules," AAAI-07 AI Video Competition, Twenty-Second Conference on Artificial Intelligence (AAAI-07), Vancouver, British Columbia, July 22–26, 2007.

P 07-5
Kaufman, K., Michalski, R. S., Pietrzykowski, J. and Wojtusiak, J., "An Integrated Multi-task Inductive Database VINLEN: Initial Implementation and Early Results," 5th International Workshop on Knowledge Discovery in Inductive Databases, Revised Selected and Invited Papers, Lecture Notes in Computer Science, 4747, 116-133, Springer, 2007.

P 07-6
Wojtusiak, J., "Handling Constrained Optimization Problems and Using Constructive Induction to Improve Representation Spaces in Learnable Evolution Model," Ph.D. Dissertation, College of Science, Reports of the Machine Learning and Inference Laboratory, MLI 07-3, George Mason University, Fairfax, VA, November, 2007.

P 07-7
Wojtusiak, J., Michalski, R. S., Simanivanh, T. and Baranova, A. V., "The Natural Induction System AQ21 and Its Application to Data Describing Patients with Metabolic Syndrome: Initial Results," Proceedings of the International Conference on Machine Learning and Applications, Cincinnati, OH, December 13-15, 2007.

P 07-8
Corriveau, A., Gergich, N., Pietrzykowski, J., Soballe, P., Pfalzer, L., McGarvey, C. and Gerber, L., "With What Does Fatigue in Women with Breast Cancer Correlate: Biological Measures, Tumor Characteristics, or Function?," 2007 Summer Research Program, The Tapestry of Science, Interdisciplinary research, Student Poster Day, NIH, Bethesda, MD, August 1, 2007.

P 07-9
Wojtusiak, J., "Handling Constrained Optimization Problems and Using Constructive Induction to Improve Representation Spaces in Learnable Evolution Model," SIGEVOlution, 2(3), 24-25, Autumn 2007.

2006

P 06-1
Michalski, R. S., "Machine Learning: A Historical Journey and Grand Challenges," Reports of the Machine Learning and Inference Laboratory, MLI 06-1, George Mason University, VA, 2006.

P 06-2
Wojtusiak, J., Michalski, R. S., Kaufman, K. and Pietrzykowski, J., "Multitype Pattern Discovery Via AQ21: A Brief Description of the Method and Its Novel Features," Reports of the Machine Learning and Inference Laboratory, MLI 06-2, George Mason University, Fairfax, VA, June, 2006.

P 06-3
Michalski, R. S., Kaufman, K., Pietrzykowski, J., Wojtusiak, J., Mitchell, S. and Seeman, W.D., "Natural Induction and Conceptual Clustering: A Review of Applications,," Reports of the Machine Learning and Inference Laboratory, MLI 06-3, George Mason University, VA, June, 2006 (Updated: August 23, 2006).

P 06-4
Wojtusiak, J. and Michalski, R. S., "The Use of Compound Attributes in AQ Learning," Proceedings of the Intelligent Information Processing and Web Mining Conference, IIPWM 06, Lecture Notes in Computer Science, Ustron, Poland, June 19-22, 2006.

P 06-5
Kaufman, K., Pietrzykowski, J., Michalski, R. S., Sniezynski, B. and Wojtusiak, J., "Learning Symbolic User Models for Intrusion Detection: A Method and Initial Results," Proceedings of the Intelligent Information Processing and Web Mining Conference, IIPWM 06, Lecture Notes in Computer Science, Ustron, Poland, June 19-22,2006.

P 06-6
Wojtusiak, J., "Initial Study on Handling Constrained Optimization Problems in Learnable Evolution Model," Proceedings of The Graduate Student Workshop at Genetic and Evolutionary Computation Conference, GECCO 2006, Seattle, WA, July 8-12, 2006.

P 06-7
Wojtusiak, J. and Michalski, R. S., "The LEM3 Implementation of Learnable Evolution Model and Its Testing on Complex Function Optimization Problems," Proceedings of Genetic and Evolutionary Computation Conference, GECCO 2006, Seattle, WA, July 8-12, 2006.

P 06-8
Seeman, W.D. and Michalski, R. S., "The CLUSTER3 System for Goal-oriented Conceptual Clustering: Method and Preliminary Results," Proceedings of The Data Mining and Information Engineering 2006 Conference, Prague, Czech Republic, July 11-13, 2006.

P 06-09
Kaufman, K., Michalski, R. S., Pietrzykowski, J. and Wojtusiak, J., "An Integrated Multi-task Inductive Database and Decision Support System VINLEN: An initial implementation and first results," Presented at the 5th International Workshop on Knowledge Discovery in Inductive Databases, KDID 06, in conjunction with ECML/PKDD, Berlin, Germany, September 18, 2006.

P 06-10
Wojtusiak, J., Michalski, R. S., Kaufman, K. and Pietrzykowski, J., "The AQ21 Natural Induction Program for Pattern Discovery: Initial Version and its Novel Features," Proceedings of The 18th IEEE International Conference on Tools with Artificial Intelligence, Washington D.C, November 13-15, 2006.

P 06-11
Michalski, R. S., Wojtusiak, J. and Kaufman, K., "Intelligent Optimization via Learnable Evolution Model," Proceedings of The 18th IEEE International Conference on Tools with Artificial Intelligence, Washington D.C, November 13-15, 2006.

P 06-12
Michalski, R. S., "Optimizing Complex Systems by Intelligent Evolution: The LEMd Method and Case Study," Bulletin of the Polish Academy of Sciences, Technical Sciences, Vol. 54, No. 4, December 2006.

P 06-13
Michalski, R. S. and Kaufman, K., "INTELLIGENT EVOLUTIONARY DESIGN: A New Approach to Optimizing Complex Engineering Systems and its Application to Designing Heat Exchangers," International Journal of Intelligent Systems, Volume 21, Issue 12, 2006.

2005

P 05-1
Kaufman, K. and Michalski, R. S., "From Data Mining to Knowledge Mining," Handbook in Statistics, Vol. 24: Data Mining and Data Visualization, Elsevier/North Holland, 47-75, 2005.

P 05-2
Michalski, R. S. and Wojtusiak, J., "Reasoning with Meta-values in AQ Learning," Reports of the Machine Learning and Inference Laboratory, MLI 05-1, George Mason University, VA, June, 2005.

P 05-3
Sniezynski, B., Szymacha, R. and Michalski, R. S., "Knowledge Visualization Using Optimized General Logic Diagrams," Proceedings of the Intelligent Information Processing and Web Mining Conference, IIPWM 05, Gdansk, Poland, June 13-16, 2005.

P 05-4
Szydlo, T., Sniezynski, B. and Michalski, R. S., "A Rules-to-Trees Conversion in the Inductive Database System VINLEN," Proceedings of the Intelligent Information Processing and Web Mining Conference, IIPWM 05, Gdansk, Poland, June 13-16, 2005.

P 05-5
Wojtusiak, J. and Michalski, R. S., "The LEM3 System for Non-Darwinian Evolutionary Computation and Its Application to Complex Function Optimization," Reports of the Machine Learning and Inference Laboratory, MLI 05-2, George Mason University, Fairfax, VA, October, 2005.

P 05-6
Michalski, R. S., Kaufman, K., Pietrzykowski, J., Sniezynski, B. and Wojtusiak, J., "Learning User Models for Computer Intrusion Detection: Preliminary Results from Natural Induction Approach," Reports of the Machine Learning and Inference Laboratory, MLI 05-3, George Mason University, VA, November, 2005.

P 05-7
Michalski, R. S. and Wojtusiak, J., "Reasoning with Missing, Not-applicable and Irrelevant Meta-values in Concept Learning and Pattern Discovery," Technical Report 2005-02, Collaborative Research Center 637, University of Bremen, Germany, July 2005.

2004

P 04-1
Domanski, P. A., Yashar, D., Kaufman, K. and Michalski, R. S., "An Optimized Design of Finned-Tube Evaporators Using the Learnable Evolution Model," Reports of the Machine Learning and Inference Laboratory, MLI 04-1, George Mason University, Fairfax, VA, February, 2004.

P 04-2
Michalski, R. S., "ATTRIBUTIONAL CALCULUS: A Logic and Representation Language for Natural Induction," Reports of the Machine Learning and Inference Laboratory, MLI 04-2, George Mason University, Fairfax, VA, April, 2004.

P 04-3
Maloof, M. and Michalski, R. S., "Incremental Learning with Partial Instance Memory," Artificial Intelligence, 154, 95-126, 2004.

P 04-4
Domanski, P. A., Yashar, D., Kaufman, K. and Michalski, R. S., "An Optimized Design of Finned-Tube Evaporators Using the Learnable Evolution Model," International Journal of Heating, Ventilating, Air-Conditioning and Refrigerating Research, 10, 201-211, April, 2004 (a final version of the report 04-1).

P 04-5
Wojtusiak, J., "AQ21 User's Guide," Reports of the Machine Learning and Inference Laboratory, MLI 04-3, George Mason University, Fairfax, VA, September, 2004.

P 04-6
Kaufman, K. and Michalski, R. S., "From Data Mining to Knowledge Mining," Reports of the Machine Learning and Inference Laboratory, MLI 04-4, George Mason University, Fairfax, VA, October, 2004.

P 04-7
Wojtusiak, J., "The LEM3 Implementation of Learnable Evolution Model: User's Guide," Reports of the Machine Learning and Inference Laboratory, MLI 04-5, George Mason University, Fairfax, VA, November, 2004.

P 04-8
Michalski, R. S., "Generating Alternative Hypotheses in AQ Learning," Reports of the Machine Learning and Inference Laboratory, MLI 04-6, George Mason University, Fairfax, VA, December, 2004.

2003

P 03-1
Kaufman, K. and Michalski, R. S., "The Development of the Inductive Database System VINLEN: A Review of Current Research," International Intelligent Information Processing and Web Mining Conference, Zakopane, Poland, 2003.

P 03-2
Cervone, G., Kaufman, K. and Michalski, R. S., "Validating Learnable Evolution Model on Selected Optimization and Design Problems," Reports of the Machine Learning and Inference Laboratory, MLI 03-1, George Mason University, Fairfax, VA, June, 2003.

P 03-3
Kaufman, K., Cervone, G. and Michalski, R. S., "An Application of Symbolic Learning to Intrusion Detection: Preliminary Results From the LUS Methodology," Reports of the Machine Learning and Inference Laboratory, MLI 03-2, George Mason University, Fairfax, VA, June, 2003.

P 03-4
Michalski, R. S., "Inferential Theory of Learning and Inductive Databases," Invited paper at the UQAM Summer Institute in Cognitive Sciences, Montreal, Canada, June 30-July 11, 2003.

2002

P 02-1
Maloof, M. and Michalski, R. S., "Incremental Learning with Partial Instance Memory," Foundations of Intelligent Systems, Lecture Notes in Artificial Intelligence, (Proceedings of the Thirteenth International Symposium on Methodologies for Intelligent Systems, Lyon, France), Vol. 2366, 16-27, Berlin:Springer-Verlag, 2002.

P 02-2
Cervone, G., Kaufman, K. and Michalski, R. S., "Recent Results from the Experimental Evaluation of the Learnable Evolution Model," Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2002, 2002.

P 02-3
Cervone, G. and Michalski, R. S., "Modeling User Behavior by Integrating AQ Learning with a Database: Initial Results," Proceedings of the IIS-02 Eleventh International Symposium on Intelligent Information Systems, Sopot, Poland, June, 2002.

P 02-4
Scorcioni, R., Cervone, G. and Ascoli, G. A., "Machine learning derived rules for the quantitative definition of neuromorphological classes," Program No. 312.15. 2002 Poster Session Washington DC, Society for Neuroscience, 2002. CD-ROM., 10th November 2002.

P 02-5
Michalski, R. S., "Attributional Ruletrees: A New Representation for AQ Learning," Reports of the Machine Learning and Inference Laboratory, MLI 02-1, George Mason University, Fairfax, VA, October, 2002 (slightly edited in May, 2004)..

2001

P 01-1
Michalski, R. S. and Kaufman, K., "The AQ19 System for Machine Learning and Pattern Discovery: A General Description and User's Guide," Reports of the Machine Learning and Inference Laboratory, MLI 01-2, George Mason University, Fairfax, VA, 2001.

P 01-2
Michalski, R. S. and Cervone, G., "Adaptive Anchoring Discretization for Learnable Evolution Model: The ANCHOR Method," Reports of the Machine Learning and Inference Laboratory, MLI 01-3, George Mason University, Fairfax, VA, 2001.

P 01-3
Cervone, G., Panait, L. A. and Michalski, R. S., " The Development of the AQ20 Learning System and Initial Experiments," Tenth International Symposium on Intelligent Information Systems, Zakopane, Poland, June, 2001.

P 01-4
Glowinski, C. and Michalski, R. S., "Discovering Multi-head Attributional Rules in Large Databases," Tenth International Symposium on Intelligent Information Systems, Zakopane, Poland, June, 2001.

P 01-5
Michalski, R. S., "Attributional Calculus: A Logic and Representation System for Natural Induction--Preliminary Version," Reports of the Machine Learning and Inference Laboratory, MLI 01-1, George Mason University, Fairfax, VA, 2001.
(Superseded by Michalski R.S., "ATTRIBUTIONAL CALCULUS: A Logic and Representation System for Natural Induction," Reports of the Machine Learning and Inference Laboratory, MLI 04-2, 2004.)

P 01-6
Michalski, R. S. and Kaufman, K., "Learning Patterns in Noisy Data: The AQ Approach," Machine Learning and its Applications, G. Paliouras, V. Karkaletsis and C. Spyropoulos (Eds.), pp. 22-38, Springer-Verlag, 2001.

P 01-7
Cervone, G. and Zucchelli, M., "An Application of Machine Learning to the Optimization of Disparity Maps," Proceedings of IASTED-01, 2001.

2000

P 00-1
Publications of the Machine Learning and Inference Laboratory 1988-1999, Reports of the Machine Learning and Inference Laboratory, MLI 00-1, R. S. Michalski and K. Kaufman (Eds.), George Mason University, Fairfax, VA, January, 2000.

P 00-2
Michalski, R. S., "LEARNABLE EVOLUTION MODEL Evolutionary Processes Guided by Machine Learning," Machine Learning , Vol. 38, pp. 9-40, 2000.

P 00-3
Kaufman, K. and Michalski, R. S., "ISHED1: Applying the LEM Methodology to Heat Exchanger Design," Reports of the Machine Learning and Inference Laboratory, MLI 00-2, George Mason University, Fairfax, VA, 2000.

P 00-4
Kaufman, K. and Michalski, R. S., "The AQ18 System for Machine Learning and Data Mining System: An Implementation and User's Guide," Reports of the Machine Learning and Inference Laboratory, MLI 00-3, George Mason University, Fairfax, VA, 2000.

P 00-5
Kaufman, K. and Michalski, R. S., "An Adjustable Rule Learner for Pattern Discovery Using the AQ Methodology," Journal of Intelligent Information Systems, 14, pp 199-216, 2000.

P 00-6
Michalski, R. S. and Kaufman, K., "Building Knowledge Scouts Using KGL Metalanguage," Fundamenta Informaticae , 40, pp 433-447, 2000.

P 00-7
Cervone, G., Michalski, R. S., Kaufman, K. and Panait, L. A., " Combining Machine Learning with Evolutionary Computation Recent Results on LEM," Proceedings of the Fifth International Workshop on Multistrategy Learning (MSL-2000), Guimarães, Portugal, pp 41-58, June 2000.

P 00-8
Michalski, R. S., Cervone, G. and Kaufman, K., " Speeding Up Evolution through Learning: LEM," Proceedings of the Ninth International Symposium on Intelligent Information Systems, Bystra, Poland, June 12-16 2000.

P 00-9
Cervone, G., Kaufman, K. and Michalski, R. S., " Experimental Validations of the Learnable Evolution Model," 2000 Congress on Evolutionary Computation, San Diego CA, pp 1064-1071, July 2000.

P 00-10
Kaufman, K. and Michalski, R. S., "Applying Learnable Evolution Model to Heat Exchanger Design," Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI-2000) and Twelfth Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-2000), Austin, TX, pp. 1014-1019, 2000.

P 00-11
Maloof, M. and Michalski, R. S., "Selecting Examples for Partial Memory Learning," Machine Learning, 41, pp. 27-52, 2000.

P 00-12
Kaufman, K. and Michalski, R. S., "A Knowledge Scout for Discovering Medical Patterns: Methodology and System SCAMP," Proceedings of the Fourth International Conference on Flexible Query Answering Systems, FQAS'2000, Warsaw, Poland, pp. 485-496, October 25-28, 2000.

P 00-13
Michalski, R. S., "Learning and Evolution: An Introduction to Non-Darwinian Evolutionary Computation," Invited paper, Twelfth International Symposium on Methodologies for Intelligent Systems, Charlotte, NC, 2000.

P 00-14
Michalski, R. S. and Brazdil, P. (Eds.), Proceedings of the Fifth International Workshop on Multistrategy Learning (MSL'00), Guimaraes, Portugal, June 11-14, 2000.

1999

P 99-1
An Overview of Research Activities in the Machine Learning and Inference Laboratory: 1998-1999, Reports of the Machine Learning and Inference Laboratory, MLI 99-1, R. S. Michalski and K. Kaufman (Eds.), George Mason University, Fairfax, VA, January, 1999.

P 99-2
Kaufman, K. and Michalski, R. S., " Learning in an Inconsistent World: Rule Selection in AQ18," Reports of the Machine Learning and Inference Laboratory, MLI 99-2, George Mason University, Fairfax, VA, May, 1999.

P 99-3
Michalski, R. S., "LEARNABLE EVOLUTION MODEL: Evolutionary Processes Guided by Machine Learning," subsumed by ML Journal paper, Reports of the Machine Learning and Inference Laboratory, MLI 99-3, George Mason University, Fairfax, VA, May, 1999.

P 99-4
Michalski, R. S. and Zhang, Q., "Initial Experiments with the LEM1 Learnable Evolution Model: An Application to Function Optimization and Evolvable Hardware," Reports of the Machine Learning and Inference Laboratory, MLI 99-4, George Mason University, Fairfax, VA, May 1999.
Slightly updated version of report MLI 98-3.

P 99-5
Coletti, M., Lash, T., Mandsager, C., Michalski, R. S. and Moustafa, R., "An Experimental Application of the Learnable Evolution Model and Genetic Algorithms to Parameter Estimation in Digital Signal Filters Design," Reports of the Machine Learning and Inference Laboratory, MLI 99-5, George Mason University, Fairfax, VA, May 1999.

P 99-6
Kaufman, K. and Michalski, R. S., "LEM2: Theory and Implementation of the Learnable Evolution Model," Reports of the Machine Learning and Inference Laboratory, MLI 99-6, George Mason University, Fairfax, VA, May 1999.

P 99-7
Kaufman, K. and Michalski, R. S., "Learning from Inconsistent and Noisy Data: The AQ18 Approach," Proceedings of the Eleventh International Symposium on Methodologies for Intelligent Systems, Warsaw, pp. 411-419, June 8-11.

P 99-8
Maloof, M. and Michalski, R. S., "Discovering Multidimensional Patterns in Large Datasets Using Knowledge Scouts," Reports of the Machine Learning and Inference Laboratory, MLI 99-7, George Mason University, Fairfax, VA, June 1999.

P 99-9
Michalski, R. S. and Kaufman, K., "AQ-PM: A Method for Partial Memory Learning," Proceedings of the Eighth Symposium on Intelligent Information Systems, Ustron, Poland, pp. 70-79, June, 1999.

P 99-10
Coletti, M., Lash, T., Mandsager, C., Michalski, R. S. and Moustafa, R., "A Measure of Description Quality for Data Mining and its Implementation in the AQ18 Learning System," Proceedings of the ICSC Congress on Computational Intelligence Methods and Applications (CIMA-99), Rochester, NY, pp. 369-375, June, 1999.

P 99-11
Cervone, G., "Comparing Performance of the Learnable Evolution Model and Genetic Algorithms on Problems in Digital Signal Filter Design," Proceedings of the 1999 Genetic and Evolutionary Computation Conference (GECCO), Orlando, July, 1999.

P 99-12
"An Experimental Application of the Learnable Evolution Model to Selected Optimization Problems," Master's Thesis, Department of Computer Science, Reports of the Machine Learning and Inference Laboratory, MLI 99-12, George Mason University, Fairfax, VA, November 1999.

1998

P 98-1
An Overview of Research Activities in the Machine Learning and Inference Laboratory: 1997-1998, Reports of the Machine Learning and Inference Laboratory, MLI 98-1, R. S. Michalski and Q. Zhang (Eds.), George Mason University, Fairfax, VA, January, 1998.

P 98-2
Duric, Z., Michalski, R. S. and Zhang, Q., "Detecting Targets in in SAR images: a Machine Learning Approach," Proceedings of the Third Asian Conference on Computer Vision, Hong Kong, January 1998.

P 98-3
Fischthal, S., "Conceptual Clusterer CLUSTER/2C++: An Object-Oriented Design and Code Documentation," Reports of the Machine Learning and Inference Laboratory, MLI 98-2, George Mason University, Fairfax, VA, 1998.

P 98-4
Kubat, M., Bratko, I. and Michalski, R. S., "A Review of Machine Learning Methods," Machine Learning and Data Mining: Methods and Applications, R. S. Michalski, I. Bratko and M. Kubat (Eds.), pp. 3-69, London: John Wiley & Sons, 1998.

P 98-5
Michalski, R. S. and Kaufman, K., "Data Mining and Knowledge Discovery: A Review of Issues and a Multistrategy Approach," Machine Learning and Data Mining: Methods and Applications, R. S. Michalski, I. Bratko and M. Kubat (Eds.), pp. 71-112, London: John Wiley & Sons, 1998.

P 98-6
Michalski, R. S., Rosenfeld, A., Duric, Z., Maloof, M. and Zhang, Q., "Learning Patterns in Images," Machine Learning and Data Mining: Methods and Applications, R. S. Michalski, I. Bratko and M. Kubat (Eds.), London, pp. 241-268, John Wiley & Sons, 1998.

P 98-7
Michalski, R. S. and Zhang, Q., "An Application of Lamarckian Evolution Model to Function Optimization," Reports of the Machine Learning and Inference Laboratory, MLI 98-3, George Mason University, Fairfax, VA, 1998.
A slightly updated version appeared as MLI 99-4.

P 98-8
Bloedorn, E. and Michalski, R. S., "Data-Driven Constructive Induction," IEEE Intelligent Systems, Special issue on Feature Transformation and Subset Selection, pp. 30-37, March/April, 1998.

P 98-9
Michalski, R. S., "Learnable Evolution: Combining Symbolic and Evolutionary Learning," Proceedings of the Fourth International Workshop on Multistrategy Learning (MSL'98), Desenzano del Garda, Italy, pp. 14-20, June 11-13, 1998.

P 98-10
Kaufman, K. and Michalski, R. S., "Discovery Planning: Multistrategy Learning in Data Mining," Proceedings of the Fourth International Workshop on Multistrategy Learning (MSL'98) , Desenzano del Garda, Italy, June 11-13, 1998.

P 98-11
Esposito, F., Michalski, R. S. and Saitta, L. (Eds.), Proceedings of the Fourth International Workshop on Multistrategy Learning (MSL'98), Desenzano del Garda, Italy, June 11-13, 1998.

P 98-12
Michalski, R. S. and Kaufman, K., "Multistrategy Data Mining via the KGL Metalanguage," Proceedings of the Seventh Symposium on Intelligent Information Systems (IIS'98) , Malbork, Poland, pp. 39-48, June 15-19, 1998.

P 98-13
Michalski, R. S., Bratko, I. and Kubat, M. (Eds.), Machine Learning and Data Mining: Methods and Applications, London, John Wiley & Sons, 1998.

1997

P 97-1
"Publication List of the Machine Learning and Inference Laboratory: 1988-1997," Reports of the Machine Learning and Inference Laboratory, MLI 97-1, George Mason University, Fairfax, VA, 1997.

P 97-2
Maloof, M. and Michalski, R. S., "Learning Symbolic Descriptions of Shape for Object Recognition In X-Ray Images," Expert Systems with Applications, Vol. 12(1), pp. 11-20, 1997.

P 97-3
Michalski, R. S. and Kaufman, K., "Data Mining and Knowledge Discovery: A Review of Issues and a Multistrategy Approach," Reports of the Machine Learning and Inference Laboratory, MLI 97-2, George Mason University, Fairfax, VA, 1997.

P 97-4
Kaufman, K. and Michalski, R. S., "KGL: A Language for Learning," Reports of the Machine Learning and Inference Laboratory, MLI 97-3, George Mason University, Fairfax, VA, 1997.

P 97-5
Fischthal, S., Lee, S. W. and Wnek, J., "Using Bayesian Classification for AQ-based Learning with Constructive Induction," Reports of the Machine Learning and Inference Laboratory, MLI 97-4, George Mason University, Fairfax, VA, 1997.

P 97-6
Zhang, Q. and Michalski, R. S., "Speeding GA-based Attribute Selection for Image Interpretation," Reports of the Machine Learning and Inference Laboratory, MLI 97-5, George Mason University, Fairfax, VA, 1997.

P 97-7
Michalski, R. S. and Imam, I. F., "On Learning Decision Structures," Fundamenta Matematicae, 31(1), dedicated to the memory of Dr. Cecylia Raucher, Polish Academy of Sciences, pp. 49-64, 1997.

P 97-8
Ko, H., "Emperical Assembly Sequence Planning: A Multistrategy Constructive Learning Approach," Machine Learning and Data Mining: Methods and Applications, R. S. Michalski, I. Bratko and M. Kubat (Eds.), London, John Wiley & Sons, 1998.

P 97-9
Lee, S. W. and Michalski, R. S., "ALPE: A System for Automatic Learning Performance Evaluation The Method and User's Guide," Reports of the Machine Learning and Inference Laboratory, MLI 97-6, George Mason University, Fairfax, VA, 1997.

P 97-10
Bloedorn, E. and Michalski, R. S., "Data-Driven Constructive Induction: A Methodology and its Applications," Reports of the Machine Learning and Inference Laboratory, MLI 97-7, George Mason University, Fairfax, VA, 1997.

P 97-11
Kaufman, K. and Michalski, R. S., "EMERALD 2: An Integrated System of Machine Learning and Discovery Programs for Education and Research, User's Guide (Updated Edition)," Reports of the Machine Learning and Inference Laboratory, MLI 97-8, George Mason University, Fairfax, VA, 1997.

P 97-12
Kaufman, K. and Michalski, R. S., "EMERALD 2: An Integrated System of Machine Learning and Discovery Programs for Education and Research, Programmer's Guide for the Sun Workstation (Updated Edition)," Reports of the Machine Learning and Inference Laboratory, MLI 97-9, George Mason University, Fairfax, VA, 1997.

P 97-13
Fischthal, S., "A Description and User's Guide for CLUSTER/2C++ A Program for Conjunctive Conceptual Clustering," Reports of the Machine Learning and Inference Laboratory, MLI 97-10, George Mason University, Fairfax, VA, 1997.

P 97-14
An Overview of Research Activities in the Machine Learning and Inference Laboratory: 1996-1997, Reports of the Machine Learning and Inference Laboratory, MLI 97-11, George Mason University, Fairfax, VA, 1997.

P 97-15
Michalski, R. S. and Wnek, J. (Eds.), Second Special Issue on Multistrategy Learning, Machine Learning, Vol. 27,No. 3, June 1997.

P 97-16
Michalski, R. S. and Kaufman, K., "Multistrategy Data Exploration Using the INLEN System: Recent Advances," Sixth International Conference on Intelligent Information Systems, Zakopane, Poland, June, 1997.

P 97-17
Aloimonos, Y., Duric, Z., Maloof, M., Michalski, R. S., Rosenfeld, A. and Zhang, Q., "Computer Vision through Learning," Reports of the Machine Learning and Inference Laboratory , MLI 97-12, George Mason University, Fairfax, VA, 1997.

P 97-18
Kafatos, M., Li, Z. and Michalski, R. S., "El Nino Teleconnections Research: Initial Results Using a Machine Learning and Discovery Approach," Reports of the Machine Learning and Inference Laboratory , MLI 97-13,, George Mason University, Fairfax, VA, 1997.

P 97-19
Zhang, Q., "Knowledge Visualizer: A Software System for Visualizing Data, Patterns and Their Relationships," Reports of the Machine Learning and Inference Laboratory , MLI 97-14, George Mason University, Fairfax, VA, September, 1997.

P 97-21
Michalski, R. S., "Seeking Knowledge in the Deluge of Facts," Fundamenta Informaticae, Vol. 30, pp. 283-297, 1997.

P 97-22
Kaufman, K., "INLEN: A Methodology and Integrated System for Knowledge Discovery in Databases," Ph.D. Dissertation, School of Information Technology and Engineering, Reports of the Machine Learning and Inference Laboratory, MLI 97-15, George Mason University, Fairfax, VA, November, 1997.

P 97-23
Michalski, R. S. and Zhang, Q., "An Easy Evaluation Program for AQ Learning Programs," Reports of the Machine Learning and Inference Laboratory, MLI 97-16, George Mason University, Fairfax, VA, December, 1997.

1996

P 96-1
"Machine Learning and Inference Laboratory: An Overview of Research and Activities," Reports of the Machine Learning and Inference Laboratory, MLI 96-1, George Mason University, Fairfax, VA, January 1996.

P 96-2
"Publication List of Machine Learning and Inference Laboratory Part 1: 1969-1987," MLI 96-2, George Mason University, Fairfax, VA, January 1996.

P 96-3
"Publication List of Machine Learning and Inference Laboratory 2: 1988-1995," MLI 96-3, George Mason University, Fairfax, VA, January 1996.

P 96-4
Kaufman, K. and Michalski, R. S., "A Multistrategy Conceptual Analysis of Economic Data," Artificial Intelligence in Economics and Management: An Edited Proceedings on the Fourth International Workshop, Boston, pp. 193-203, Kluwer Academic Publishers, 1996.

P 96-5
Michalski, R. S., Rosenfeld, A., Aloimonos, Y., Duric, Z., Maloof, M. and Zhang, Q., "Progress On Vision Through Learning: A Collaborative Effort of George Mason University and University of Maryland," Proceedings of the Image Understanding Workshop, Palm Springs, CA, Feburary, 1996.

P 96-7
Michalski, R. S., Zhang, J., Maloof, M. and Bloedorn, E., "The MIST Methodology and its Application to Natural Scene Interpretation," Proceedings of the Image Understanding Workshop, Palm Springs, CA, pp. 1473-1479, Feburary, 1996.

P 96-8
Duric, Z., Rivlin, E. and Rosenfeld, A., "Learning an Object's Function by Observing the Object in Action," Proceedings of the Image Understanding Workshop, Palm Springs, CA, February, 1996.

P 96-9
Maloof, M., Duric, Z., Michalski, R. S. and Rosenfeld, A., "Recognizing Blasting Caps in X-Ray Images," Proceedings of the Image Understanding Workshop, Palm Springs, CA, Feburary, 1996.

P 96-10
Imam, I., "The AQDT-2 USER'S GUIDE: A Machine Learning Program for Learning Task-oriented Decision Structures from Decision Rules," Reports of the Machine Learning and Inference Laboratory, MLI 96-4, George Mason University, Fairfax, VA, March 1996.

P 96-11
Imam, I., "The AQDT-2 PROGRAMMER'S GUIDE: A Machine Learning Program for Learning Task-oriented Decision Structures from Decision Rules," Reports of the Machine Learning and Inference Laboratory, MLI 96-5, George Mason University, Fairfax, VA, March 1996.

P 96-12
Michalski, R. S. and Wnek, J. (Eds.), Proceedings of the Third International Workshop on Multistrategy Learning (MSL-96), Harpers Ferry, WV, May 23-25, 1996.

P 96-13
Alkharouf, N. W. and Michalski, R. S., "Multistrategy Task-Adaptive Learning Using Dynamic Interlaced Hierarchies: A Methodology and Initial Implementation of INTERLACE," Proceedings of the Third International Workshop on Multistrategy Learning (MSL-96), Harpers Ferry, WV, pp. 117-124, May 23-25, 1996.

P 96-14
Kaufman, K., "Addressing Knowledge Discovery Problems in a Multistrategy Framework," Proceedings of the Third International Workshop on Multistrategy Learning (MSL-96), Harpers Ferry, WV, pp. 305-312, May 23-25, 1996.

P 96-15
Bloedorn, E. and Michalski, R. S., "The AQ17-DCI System for Data-Driven Constructive Induction and Its Application to the Analysis of World Economics," Proceedings of the Ninth International Symposium on Methodologies for Intelligent Systems (ISMIS-96), Zakopane, Poland, June 10-13, 1996.

P 96-16
Imam, I. and Michalski, R. S., "An Empirical Comparison Between Learning Decision Trees from Examples and from Decision Rules," Proceedings of the Ninth International Symposium on Methodologies for Intelligent Systems (ISMIS-96), Zakopane, Poland, June 10-13.

P 96-17
Imam, I., "Do We Efficiently Estimate the Attributional Relevancy to Learning Systems?," Proceedings of the Ninth International Symposium on Methodologies for Intelligent Systems (ISMIS-96), Zakopane, Poland, June 10-13, 1996.

P 96-18
Duric, Z., Fayman, J. A. and Rivlin, E., "Function From Motion," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 18, No. 6, pp. 579-591, June, 1996.

P 96-19
Wnek, J., Kaufman, K., Bloedorn, E. and Michalski, R. S., "Inductive Learning System AQ15c: The Method and User's Guide," Reports of the Machine Learning and Inference Laboratory, MLI 96-6, George Mason University, Fairfax, VA, August, 1996.

P 96-20
Bloedorn, E., Mani, I. and MacMillan, T. R., "Machine Learning of User Profiles: Representational Issues," Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), Portland, OR, August, 1996.

P 96-21
Kaufman, K. and Michalski, R. S., "A Method for Reasoning with Structured and Continuous Attributes in the INLEN-2 Multistrategy Knowledge Discovery System," Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96), Portland, OR, pp. 232-237, August, 1996.

P 96-22
Duric, Z. and Rosenfeld, A., "Image Sequence Stabilization in Real Time," Real-Time Imaging, Vol. 2, pp. 271-284, 1996.

P 96-23
Bloedorn, E., "Multistrategy Constructive Induction," Ph.D. Dissertation,Reports of the Machine Learning and Inference Laboratory, MLI 96-7, School of Information Technology and Engineering,George Mason University, Fairfax, VA, 1996.

P 96-24
Maloof, M. and Michalski, R. S., "Partial Memory Learning System AQ-PM: The Method and User's Guide," Reports of the Machine Learning and Inference Laboratory, MLI 96-8, George Mason University, Fairfax, VA, 1996.

P 96-25
Maloof, M., "Progressive Partial Memory Learning," Ph.D. Dissertation, Reports of the Machine Learning and Inference Laboratory, MLI 96-9, School of Information Technology and Engineering, George Mason University, Fairfax, VA, 1996.

P 96-26
Lee, S. W., "Multistrategy Learning: An Empirical Study with AQ + Bayesian Approach," Reports of the Machine Learning and Inference Laboratory, MLI 96-10, George Mason University, Fairfax, VA, 1996.

P 96-27
Lee, S. W., "WWW-AQ: World Wide Web Interface for the AQ Learning System Users and Programmers Guide," Reports of the Machine Learning and Inference Laboratory, MLI 96-11, George Mason University, Fairfax, VA, 1996.

P 96-28
Zhang, Q., Duric, Z. and Michalski, R. S., "Target Detection in SAR Images Using the MIST/AQ Method," Reports of the Machine Learning and Inference Laboratory, MLI 96-12, George Mason University, Fairfax, VA, 1996.

1995

P 95-1
"Center for Machine Learning and Inference: An Overview of Research and Activities," Reports of the Machine Learning and Inference Laboratory, MLI 95-1, George Mason University, Fairfax, VA, January, 1995.

P 95-2
Maloof, M. and Michalski, R. S., "A Partial Memory Incremental Learning Methodology and its Application to Computer Intrusion Detection," Reports of the Machine Learning and Inference Laboratory, MLI 95-2, George Mason University, Fairfax, VA, March 1995.

P 95-3
Bloedorn, E., Imam, I., Kaufman, K., Maloof, M., Michalski, R. S. and Wnek, J., "HOW DID AQ FACE THE EAST-WEST CHALLENGE? An Analysis of the AQ Family's Performance in the 2nd International Competition of Machine Learning Programs," Reports of the Machine Learning and Inference Laboratory, MLI 95-3, George Mason University, Fairfax, VA, March 1995.

P 95-4
Wnek, J., Kaufman, K., Bloedorn, E. and Michalski, R. S., "Inductive Learning System AQ15c: The Method and User's Guide," Reports of the Machine Learning and Inference Laboratory, MLI 95-4, George Mason University, Fairfax, VA, March 1995.

P 95-5
Wnek, J., "DIAV 2.0 User Manual: Specification and Guide through the Diagrammatic Visualization System," Reports of the Machine Learning and Inference Laboratory, MLI 95-5, George Mason University, Fairfax, VA, 1995.

P 95-6
Arciszewski, T., Michalski, R. S. and Dybala, T., "STAR Methodology-Based Learning about Construction Accidents and their Prevention," Journal of Construction Automation, Vol. 4, pp. 75-85, 1995.

P 95-7
"Proceedings of the First International Workshop on Intelligent Adaptive Systems (IAS-95)," , I. Imam and J. Wnek (Eds.), Melbourne Beach, FL, April 26, 1995.

P 95-8
Bloedorn, E. and Wnek, J., "Constructive Induction-based Learning Agents: An Architecture and Preliminary Experiments," Proceedings of the First International Workshop on Intelligent Adaptive Systems (IAS-95), Melbourne Beach, FL, pp. 38-49, April 26, 1995.

P 95-9
Imam, I., "Intelligent Agents for Management of Learning: An Introduction and a Case Study," Proceedings of the First International Workshop on Intelligent Adaptive Systems (IAS-95), Melbourne Beach, FL, pp. 95-106, April 26, 1995.

P 95-10
Arciszewski, T., Michalski, R. S. and Wnek, J., "Constructive Induction: The Key to Design Creativity," Reports of the Machine Learning and Inference Laboratory, MLI 95-6, Machine Learning and Inference Laboratory, George Mason University, Fairfax, VA, April 1995.

P 95-11
Chen, Q. and Arciszewski, T., "Machine Learning of Bridge Design Rules: A Case Study," Proceedings of the 2nd ASCE Congress on Computing in Civil Engineering, Atlanta GA, June, 1995.

P 95-12
Kaufman, K., Kerschberg, L. and Ribeiro, J., "Knowledge Discovery from Multiple Databases," Proceedings of the IASTED/ISMM International Conference on Intelligent Information Management Systems, Washington, D.C., June, 1995.

P 95-13
Michalski, R. S. and Wnek, J., "Learning Hybrid Descriptions," Proceedings of the 4th International Symposium on Intelligent Information Systems, Augustow, Poland, June 5-9, 1995.

P 95-14
Michalski, R. S., "Learning and Cognition," Invited talk at 2nd International World Conference on the Foundations of Artificial Intelligence, Paris, July 3-7, 1995.

P 95-15
Arciszewski, T., Szczepanik, W. and Wnek, J., "Empirical Performance Comparison of Two Symbolic Learning Systems Based On Selective And Constructive Induction," Proceedings of the IJCAI-95 Workshop on Machine Learning in Engineering, Montreal, Canada, August, 1995.

P 95-16
Ribeiro, J., Kaufman, K. and Kerschberg, L., "Knowledge Discovery from Multiple Databases," Proceedings of the First International Conference on Knowledge Discovery and Data Mining (KDD-95), Montreal, Canada, pp. 240-245, August, 1995.

P 95-17
Maloof, M. and Michalski, R. S., "Learning Symbolic Descriptions of 2D Shapes for Object Recognition in X-ray Images," Proceedings of the 8th International Symposium on Artificial Intelligence, Monterrey, Mexico, October 17-20, 1995.

P 95-18
Maloof, M. and Michalski, R. S., "A Method for Partial-Memory Incremental Learning and its Application to Computer Intrusion Detection," Proceedings of the 7th IEEE International Conference on Tools with Artificial Intelligence, Herndon, VA, 1995.

P 95-19
De Jong, K. and Vafaie, H., "Genetic Algorithm as a Tool for Restructuring Feature Space Representations," Proceedings of the 7th IEEE International Conference on Tools with Artificial Intelligence, Herndon, VA, 1995.

P 95-20
Ibrahim, M. and Imam, I., "Deriving Task-oriented Decision Structures From Decision Rules," Ph.D. dissertation School of Information Technology and Engineering, Reports of the Machine Learning and Inference Laboratory, MLI 95-7, George Mason University, Fairfax, VA, October 1995.

P 95-21
Michalski, R. S. and Ram, A., "Learning as Goal-Driven Inference," Goal-Driven Learning, A. Ram and D. B Leake (Eds.), MIT Press/Bradford Books

P 95-22
Maloof, M. and Michalski, R. S., "Learning Evolving Concepts Using Partial Memory Approach," Proceedings of the AAAI 1995 Fall Symposium on Active Learning, Cambridge, MA, November 10-12, 1995.

P 95-23
Arciszewski, T., Michalski, R. S. and Wnek, J., "Constructive Induction: the Key to Design Creativity," Proceedings of the Third International Round-Table Conference on Computational Models of Creative Design, Heron Island, Queensland, Australia, pp. 397-425, December 3-7, 1995.

P 95-24
Zhang, J. and Michalski, R. S., "An Integration of Rule Induction and Exemplar- Based Learning for Graded Concepts," Machine Learning, Vol.21, No.3, pp. 235-268, Kluwer Academic Publishers, December 1995.

P 95-25
"Presentation Notes of the Annual Review of Research in Machine Learning and Inference," , J. Wnek and R. S. Michalski (Eds.), Machine Learning and Inference Laboratory, George Mason University, Fairfax, VA, May 19, 1995.

P 95-26
Arciszewski, T., Bloedorn, E., Michalski, R. S., Mustafa, M. and Wnek, J., "Machine Learning in Engineering Design: A Methodology and Case Study," Reports of the Machine Learning and Inference Laboratory, MLI 95-8, George Mason University, Fairfax, VA, December, 1995.

1994

P 94-1
Michalski, R. S. and Tecuci, G. (Eds.), Machine Learning -A Multistrategy Approach Vol IV, San Mateo, CA., Morgan Kaufmann, 1994.

P 94-2
Bala, J. W., De Jong, K. A. and Pachowicz, P. W., "Multistrategy Learning from Engineering Data by Integrating Inductive Generalization and Genetic Algorithms," Machine Learning: A Multistrategy Approach, Vol. IV, San Mateo, CA, 471-488, Morgan Kaufmann, 1994.

P 94-3
De Garis, H., "Genetic Programming: Evolutionary Approaches to Multistrategy Learning," Machine Learning: A Multistrategy Approach, Vol. IV, San Mateo, CA, 549-578, Morgan Kaufmann, 1994.

P 94-4
Michalski, R. S., "Inferential Theory of Learning: Developing Foundations for Multistrategy Learning," Machine Learning: A Multistrategy Approach, Vol. IV, San Mateo, CA, pp. 3-61, Morgan Kaufmann, 1994.

P 94-5
De Jong, K. A. and Vafaie, H., "Improving the Performance of a Rule Induction System Using Genetic Algorithms," Machine Learning: A Multistrategy Approach, Vol. IV, San Mateo, CA, 453-470, Morgan Kaufmann, 1994.

P 94-6
Wnek, J. and Michalski, R. S., "Comparing Symbolic and Subsymbolic Learning: Three Studies," Machine Learning: A Multistrategy Approach, Vol. IV, R. S. Michalski and G. Tecuci (Eds.), San Mateo, CA, 489-519, Morgan Kaufmann, 1994.

P 94-7
Hieb, M. R. and Wnek, J., "Bibliography of Multistrategy Learning Research," Machine Learning: A Multistrategy Approach, Vol. IV, San Mateo, CA, 657-730, Morgan Kaufmann, 1994.

P 94-8
Zhang, J., "Learning Graded Concept Descriptions by Integrating Symbolic and Subsymbolic Approaches," Machine Learning: A Multistrategy Approach, Vol. IV, San Mateo, CA, 431-452, Morgan Kaufmann, 1994.

P 94-9
Wnek, J. and Michalski, R. S., "Hypothesis-driven Constructive Induction in AQ17-HCI: A Method and Experiments," Machine Learning, Vol. 14, No. 2, pp. 139-168, 1994.

P 94-10
Imam, I. and Vafaie, H., "Feature Selection Methods: Genetic Algorithm vs. Greedy-like Search," Proceedings of the 3rd International Fuzzy Systems and Intelligent Control Conference, Louisville, KY, March 1994.

P 94-11
Wnek, J. and Michalski, R. S., "Symbolic Learning of M-of-N Concepts," Reports of the Machine Learning and Inference Laboratory, MLI 94-1, School of Information Technology and Engineering, George Mason University, Fairfax, VA, April 1994.

P 94-12
Bloedorn, E., Michalski, R. S. and Wnek, J., "Matching Methods with Problems: A Comparative Analysis of Constructive Induction Approaches," Reports of the Machine Learning and Inference Laboratory, MLI 94-2, School of Information Technology and Engineering, George Mason University, Fairfax, VA, May 1994.

P 94-13
Imam, I. and Vafaie, H., "An Empirical Comparison Between Global and Greedy-like Search for Feature Selection," Proceedings of the 7th Florida Artificial Intelligence Research Symposium (FLAIRS-94), Pensacola Beach, FL, pp. 66-70, May 1994.

P 94-14
Bloedorn, E. and Tischer, L., "An Application of Machine Learning to GIS Analysis," Proceedings of the ESRI-94 User Conference, CA, May 1994.

P 94-15
Imam, I., "An Experimental Study of Discovery in Large Temporal Databases," Proceedings of the Seventh International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE-94), Austin, TX, pp. 171-180, June 1994.

P 94-16
Arciszewski, T., Bloedorn, E., Michalski, R. S., Mustafa, M. and Wnek, J., "Machine Learning of Design Rules: Methodology and Case Study," ASCE Journal of Computing in Civil Engineering, Vol. 8, No. 3, pp. 286-308, July 1994.

P 94-17
Sazonov, V. N. and Wnek, J., "Hypothesis-driven Constructive Induction Approach to Expanding Neural Networks," Working Notes of the ML-COLT'94 Workshop on Constructive Induction and Change of Representation, New Brunswick, NJ, July 1994.

P 94-18
Wnek, J. and Michalski, R. S., "Discovering Representation Space Transformations for Learning Concept Descriptions Combining DNF and M-of-N Rules," Working Notes of the ML-COLT'94 Workshop on Constructive Induction and Change of Representation, New Brunswick, NJ, July 1994.

P 94-19
Arciszewski, T., Hoda, S. K., Khasnabis, S. and Ziarko, W., "Machine Learning in Transportation Engineering: A Feasibility Study," Journal of Applied Artificial Intelligence, Vol. 8, No. 1, 1994.

P 94-20
Arciszewski, T., Borkowski, A., Dybala, T., Racz, J. and Wojan, P., "Empirical Comparison for Symbolic and Subsymbolic Learning Systems," Proceedings of the First International ASCE Congress on Computing in Civil Engineering, Washington, D.C., 1994.

P 94-21
Arciszewski, T., "Machine Learning in Engineering Design," Proceedings of the Conference on Intelligent Information Systems, Institute of Computer Science, Polish Academy of Sciences, Wigry, Poland, 1994.

P 94-22
Arciszewski, T. and Michalski, R. S., "Inferential Design Theory: A Conceptual Outline," Proceedings of the Third International Conference on Artificial Intelligence in Design, Lausanne, Switzerland, 1994.

P 94-23
Imam, I. and Michalski, R. S., "From Fact to Rules to Decisions: An Overview of the FRD-1 System," Proceedings of the AAAI-94 Workshop on Knowledge Discovery in Databases, Seattle, WA, pp. 229-236, August, 1994.

P 94-24
Kaufman, K., "Comparing International Development Patterns Using Multi-operator Learning and Discovery Tools," Proceedings of the AAAI-94 Workshop on Knowledge Discovery in Databases, Seattle, WA, pp. 431-440, August, 1994.

P 94-25
Maloof, M. and Michalski, R. S., "Learning Descriptions of 2D Shapes for Object Recognition and X-Ray Images," Reports of the Machine Learning and Inference Laboratory, MLI 94-4, George Mason University, Fairfax, VA, October 1994.

P 94-26
Michalski, R. S. and Ram, A., "Learning as Goal-Driven Inference," Reports of the Machine Learning and Inference Laboratory, MLI 94-5, George Mason University, Fairfax, VA, October 1994.

P 94-27
Michalski, R. S., Rosenfeld, A. and Aloimonos, Y., "Machine Vision and Learning: Research Issues and Directions," Reports of the Machine Learning and Inference Laboratory, Reports of the Center for Automation Research CAR-TR-739, MLI 94-6, CS-TR-3358, George Mason University, Fairfax, VA, University of Maryland, College Park, MD, October 1994.

P 94-28
Michalski, R. S. and Imam, I., "Learning Problem-Oriented Decision Structures from Decision Rules: The AQDT-2 System," Lecture Notes in Artificial Intelligence, Methodology for Intelligent Systems of the 8th International Symposium on Methodology for Intelligent Systems (ISMIS-94), No. 869, pp. 416-426, October, 1994.

P 94-29
Michaels, G. S., "Bioinformatics or Biology?," Chemical Design Automation News, Vol. 8, pp. 1-34, 1994.

P 94-30
Michaels, G. S., Rushforth, N., Taylor, R. and Zull, J. E., "Nucleic Acid Sequences Coding for Internal Antisence Peptides: Are There Implications for Protein Folding and Evolution?," Nucleic Acid Research, 1994.

P 94-31
Michalski, R. S. and Wnek, J., "Conceptual Transition from Logic to Arithmetic," Reports of the Machine Learning and Inference Laboratory, MLI 94-7, George Mason University, Fairfax, VA, December 1994.

P 94-32
Michalski, R. S., "Seeking Knowledge in the Flood of Facts," Proceedings of the Conference on Intelligent Information Systems, Institute of Computer Science, Polish Academy of Sciences, Wigry, Poland, pp. 85-102, 1994.

P 94-33
Bala, J. W. and Pachowicz, P. W., "A Noise-Tolerant Approach to Symbolic Learning from Sensory Data," Journal of Intelligent and Fuzzy Systems, Vol. 2, pp. 347-361, John Wiley & Sons, Inc., 1994.

P 94-34
Bala, J. W., Michalski, R. S. and Pachowicz, P. W., "Progress on Vision Through Learning at George Mason University," Proceedings of the ARPA Image Understanding Workshop, November 13-16, 1994.

1993

P 93-1
Michalski, R. S., "Toward a Unified Theory of Learning: Multistrategy Task-adaptive Learning," Readings in Knowledge Acquisition and Learning: Automating the Construction and Improvement of Expert Systems, B. G. Buchanan and D. C. Wikins (Eds.), San Mateo, CA, Morgan Kaufmann, 1993.

P 93-2
Mechelen, I.V., "A Theory and Methodology of Inductive Learning," Readings in Knowledge Acquisition and Learning: Automating the Construction and Improvement of Expert Systems, San Mateo, CA, Morgan Kaufmann, 1993.

P 93-3
Categories and Concepts: Theoretical Views and Inductive Data Analysis, New York, Academic Press, 1993.

P 93-4
Michalski, R. S., "Beyond Prototypes and Frames: The Two-tiered Concept Representation," Categories and Concepts: Theoretical Views and Inductive Data Analysis, I. Van Mechelen, J. Hampton, R. S. Michalski and P. Theuns (Eds.), New York, Academic Press, 1993.

P 93-5
Michalski, R. S., "Learning = Inferencing + Memorizing: Basic Concepts of Inferential Theory of Learning and Their Use for Classifying Learning Processes," Foundations of Knowledge Acquisition, Vol. 2: Machine Learning, pp. 1-41, 1993.

P 93-6
Bergadano, F., Matwin, S., Michalski, R. S. and Zhang, J., "Learning Flexible Concepts Using a Two-tiered Representation," Foundations of Knowledge Acquisition, Vol. 2: Machine Learning, pp. 145-202, 1993.

P 93-7
Michalski, R. S., Pachowicz, P. W., Rosenfeld, A. and Aloimonos, Y., "Machine Learning and Vision: Research Issues and Promising Directions," NSF/DARPA Workshop on Machine Learning and Vision (MLV-92), HarpersFerry, WV, October 15-17, 1992; Reports of the Machine Learning and Inference Laboratory, MLI 93-1, School of Information Technology and Engineering, George Mason University, February, 1993.

P 93-8
Wnek, J., "Hypothesis-driven Constructive Induction," Ph.D. dissertation, Reports of the Machine Learning and Inference Laboratory, MLI 93-2, School of Information Technology and Engineering, George Mason University, March 1993.

P 93-9
Bala, J. W., "Learning to Recognize Visual Concepts: Development and Implementation of a Method for Texture Concept Acquisition Through Inductive Learning," Ph.D. dissertation, Reports of the Machine Learning and Inference Laboratory, MLI 93-3, School of Information Technology and Engineering, George Mason University, March 1993.

P 93-10
Michalski, R. S., Bala, J. W. and Pachowicz, P. W., "GMU Research on Learning in Vision: Initial Results," Proceedings of the DARPA Image Understanding Workshop, Washington D.C., April 18-21, 1993.

P 93-11
Bloedorn, E., Wnek, J. and Michalski, R. S., "Multistrategy Constructive Induction: AQ17-MCI," Reports of the Machine Learning and Inference Laboratory, MLI 93-4, School of Information Technology and Engineering, George Mason University, May 1993.

P 93-12
Hieb, M. R. and Michalski, R. S., "A Knowledge Representation System Based on Dynamically Interlaced Hierarchies: Basic Ideas and Examples," Reports of the Machine Learning and Inference Laboratory, MLI 93-5, School of Information Technology and Engineering, George Mason University, May 1993.

P 93-13
Bloedorn, E., Michalski, R. S. and Wnek, J., "Multistrategy Constructive Induction: AQ17-MCI," Proceedings of the Second International Workshop on Multistrategy Learning (MSL93), Harpers Ferry, WV, pp. 188-203, Morgan Kaufmann, May 26-29, 1993.

P 93-14
Hieb, M. R. and Michalski, R. S., "Multitype Inference in Multistrategy Task-adaptive Learning: Dynamic Interlaced Hierarchies," Proceedings of the Second International Workshop on Multistrategy Learning (MSL93), Harpers Ferry, WV, 3-18, Morgan Kaufmann, May 26-29, 1993.

P 93-15
Proceedings of the 2nd International Workshop on Multistrategy Learning (MSL93), Harpers Ferry, WV, Morgan Kaufmann, May 26-29, 1993.

P 93-16
Imam, I. and Michalski, R. S., "Learning Decision Trees from Decision Rules: A Method and Initial Results from a Comparative Study," Reports of the Machine Learning and Inference Laboratory, MLI 93-6, School of Information Technology and Engineering, George Mason University, May 1993.

P 93-17
Wnek, J., Michalski, R. S. and Arciszewski, T., "An Application of Constructive Induction to Engineering Design," Reports of the Machine Learning and Inference Laboratory, MLI 93-7, School of Information Technology and Engineering, George Mason University, May 1993.

P 93-18
Imam, I. and Michalski, R. S., "Should Decision Trees Be Learned from Examples or from Decision Rules?," Lecture Notes in Artificial Intelligence, Proceedings of the 7th International Symposium on Methodologies for Intelligent Systems, ISMIS, Trondheim, Norway, Springer Verlag, June 15-18, 1993.

P 93-19
Imam, I., Michalski, R. S. and Kerschberg, L., "Discovering Attribute Dependence in Databases by Integrating Symbolic Learning and Statistical Analysis Techniques," Proceedings of the AAAI-93 Workshop on Knowledge Discovery in Databases, Washington, D.C., July 11-12, 1993.

P 93-20
Michalski, R. S. and Tecuci, G., "Multistrategy Learning," Tutorial at the National Conference on Artificial Intelligence, AAAI-93, Washington D.C., July 11-12, 1993.

P 93-21
Michalski, R. S., "Inferential Theory of Learning as a Conceptual Basis for Multistrategy Learning," Machine Learning, Special Issue on Multistrategy Learning, Vol. 11, pp. 111-151, 1993.

P 93-22
Wnek, J., Michalski, R. S. and Arciszewski, T., "An Application of Constructive Induction to Engineering Design," Proceedings of the IJCAI-93 Workshop on AI in Design, Chambery France, August 1993.

P 93-23
Michalski, R. S. and Tecuci, G., "Multistrategy Learning," Tutorial at the International Joint Conference on Artificial Intelligence, IJCAI-93, Chambery, France, August, 1993.

P 93-24
Kaufman, K., Michalski, R. S. and Schultz, A., "EMERALD 2 An Integrated System of Machine Learning and Discovery Programs for Education and Research User's Guide," Reports of the Machine Learning and Inference Laboratory, MLI 93-8, School of Information Technology and Engineering, George Mason University, Fairfax, VA, September ,1993.

P 93-25
Kaufman, K., Schultz, A. and Michalski, R. S., "EMERALD 2 An Integrated System of Machine Learning and Discovery Programs for Education and Research Programmers Guide for the SUN Workstation," Reports of the Machine Learning and Inference Laboratory, MLI 93-9, School of Information Technology and Engineering, George Mason University, Fairfax, VA, September, 1993.

P 93-26
Kaufman, K. and Michalski, R. S., "EMERALD 2: An Integrated System of Machine Learning and Discovery Programs to Support Education and Experimental Research," Reports of the Machine Learning and Inference Laboratory, MLI 93-10, School of Information Technology and Engineering, George Mason University, Fairfax, VA, September, 1993.

P 93-27
Bala, J. W., Michalski, R. S. and Wnek, J., "The PRAX Approach to Learning a Large Number of Texture Concepts," American Association for Artificial Intelligence(AAAI) Fall Symposium on Machine Learning in Computer Vision, Menlo Park, CA, AAAI Press, October, 1993.

P 93-28
Bala, J. W. and Pachowicz, P. W., "Issues in Learning from Noisy Sensory Data," Technical Report FS-93-04 Machine Learning in Computer Vision What Why and How AAAI Fall Symposium on Machine Learning in Computer Vision, Menlo Park, CA, AAAI Press, October 1993.

P 93-29
Pachowicz, P. W., "Integration of Machine Learning and Vision into an Active Agent Paradigm on the Example of Face Recognition Problem," Technical Report FS-93-04 Machine Learning in Computer Vision What Why and How AAAI Fall Symposium on Machine Learning in Computer Vision, Menlo Park, CA, AAAI Press, October 1993.

P 93-30
Imam, I. and Michalski, R. S., "Learning Decision Trees from Decision Rules A Method and Initial Results from a Comparative Study," Journal of Intelligent Information Systems JIIS, Vol. 2 No. 3, pp 279-304, 1993.

P 93-31
Vafaie, H. and De Jong, K. A., "Robust Feature Selection Algorithms," Proceedings of the 5th International Conference on Tools with Artificial Intelligence, Boston, MA, November, 1993.

P 93-32
Michalski, R. S. and Wnek, J., "Constructive Induction An Automated Improvement of Knowledge Representation Spaces for Machine Learning," Reports of the Machine Learning and Inference Laboratory, MLI 93-11, School of Information Technology and Engineering, George Mason University, Fairfax, VA, November, 1993.

P 93-33
Bloedorn, E., Wnek, J., Michalski, R. S. and Kaufman, K., "AQ17 A Multistrategy Learning System The Method and Users Guide," Reports of the Machine Learning and Inference Laboratory, MLI 93-12, School of Information Technology and Engineering, George Mason University, Fairfax, VA, November, 1993.

P 93-34
Guillen, Jr., L. E. and Wnek, J., "Investigation of Hypothesis-driven Constructive Induction in AQ17," Reports of the Machine Learning and Inference Laboratory, MLI 93-13, School of Information Technology and Engineering, George Mason University, Fairfax, VA, December 1993.

P 93-35
Hieb, M. R. and Michalski, R. S., "Multitype Inference in Multistrategy Task-adaptive Learning Dynamic Interlaced Hierarchies," Informatica: An International Journal of Computing and Informatics, Vol 17 No 4, pp 399-412, December, 1993.

P 93-36
Michalski, R. S. and Tecuci, G., "Multistrategy Learning," Encyclopedia of Microcomputers, Vol 12, New York, Marcel Dekker, 1993.

P 93-37
Michalski, R. S. and Wnek, J., "Constructive Induction An Automated Improvement of Knowledge Representation Spaces for Machine Learning," Proceedings of the 2nd Conference on Practical Aspects of Artificial Intelligence, Augustow, IPI PAN, Warszawa, Poland, pp 188-236, 1993.

P 93-38
Khasnabis, S., Arciszewski, T., Hoda, S. K. and Ziarko, W., "Automated Knowledge Acquisition for Control of an Urban Rail Corridor," Proceedings of the Third International Conference on the Applications of Artificial Intelligence to Civil and Structural Engineering, Edinburgh, Scotland, 1993.

P 93-39
Arciszewski, T. and Usmen, M., "Applications of Machine Learning to Construction Safety," Proceedings of the International Conference on Management of Information Technology for Construction, Singapore, 1993.

P 93-40
Arciszewski, T., Khan, T. L. and Ziarko, W., "Learning Conceptual Design Rules A Rough Sets Approach," Proceedings of the International Workshop on Rough Sets, Banff, Alberta, Canada, 1993.

P 93-41
Arciszewski, T., "Learning Engineering An Outline," Proceedings of the ASCE Conference on Computing in Civil Engineering, Anaheim, California, 1993.

P 93-42
Seligman, L. and Kerschberg, L., "An Active Database Approach to Consistency Management in Heterogeneous Data-and Knowledge-based Systems," International Journal of Cooperative and Intelligent Systems, Vol 2 No 2, October 1993.

P 93-43
Seligman, L. and Kerschberg, L., "Federated Knowledge and Database Systems A New Architecture for Integrating of AI and Database Systems," Advances in Databases and Artificial Intelligence, L. Delcambre and F. Petry (Eds.), Vol 1 The Landscape of Intelligence in Database and Information Systems, JAI Press, 1993.

P 93-44
Yoon, J. P. and Kerschberg, L., "A Framework for Knowledge Discovery and Evolution in Databases," IEEE Transactions on Knowledge and Data Engineering, Vol 5 No 6, December 1993.

P 93-45
Michalski, R. S., Carbonell, T. J., Mitchell, T. M. and Kodratoff, Y. (Eds.), Apprentissage Symbolique Une Approche de lIntelligence Artificielle Tome I-II French compilation of Machine Learning An Artificial Intelligence Approach, Vol I-III, Cepadues-Editions, 1993.

P 93-46
Michalski, R. S. (Ed.), Multistrategy Learning, Kluwer Academic Publishers, 1993.

P 93-47
Michaels, G. S., Taylor, R., Hagstrom, R., Price, M. and Overback, R., "Searching for Genomic Organizational Motifs Explorations of the E coli Chromosome," Computers in Chemistry, Vol 17, pp209-217, 1993.

P 93-48
Michaels, G. S., Taylor, R., Hagstrom, R., Price, M. and Overback, R., "Comparative Analysis of Genomic Data A Global Look and Structural and Regulatory Features," Proceedings of the Second International Conference of Bioinformatics Supercomputing and Complex Genome Analysis, H. A Lim (Ed.), River Edge, NJ, pp 297-308, World Scientific Publishing Co, 1993.

1992

P 92-1
Bergadano, F., Matwin, S., Michalski, R. S. and Zhang, J., "Learning Two-tiered Descriptions of Flexible Concepts: The POSEIDON System," Machine Learning, Vol. 8, No. 1, pp. 5-43, January, 1992.

P 92-2
Wnek, J., "Version Space Transformation with Constructive Induction: The VS* Algorithm," Reports of the Machine Learning and Inference Laboratory, MLI 92-1, George Mason University, Fairfax, VA, January 1992.

P 92-3
Michalski, R. S. and Wnek, J., "Hypothesis-driven Constructive Induction in AQ17: A Method and Experiments," Reports of the Machine Learning and Inference Laboratory, MLI 92-2, George Mason University, Fairfax, VA, January, 1992.

P 92-4
De Jong, K. A. and Spears, W., "A Formal Analysis of the Role of Multi-point Crossover in Genetic Algorithms," Annals of Mathematics and Artificial Intelligence, Vol. 5, No. 1, January, 1992.

P 92-5
Fermanian, T. and Michalski, R. S., "AgAssistant: A New Generation Tool for Developing Agricultural Advisory Systems,in Mann," Expert Systems in the Developing Countries: Practice and Promise, Westview Press Publication, 1992.

P 92-6
Michalski, R. S. and Chilausky, R., "Knowledge Acquisition by Encoding Expert Rules versus Computer Induction from Examples: A Case Study Involving Soybean Pathology," Artificial Intelligence and Software Engineering, Alex Publishing Corporation, 1992.

P 92-7
Michalski, R. S., Kerschberg, L., Kaufman, K. and Ribeiro, J., "Searching for Knowledge in Large Databases," Proceedings of the First International Conference on Expert Systems and Development, Cairo Egypt, April, 1992.

P 92-8
Bala, J. W., Michalski, R. S. and Wnek, J., "The Principal Axes Method for Constructive Induction," Proceedings of the 9th International Conference on Machine Learning, Aberdeen, Scotland, July, 1992.

P 92-9
Tecuci, G., "Cooperation in Knowledge Base Refinement," Proceedings of the Ninth International Machine Learning Conference (ML92), Aberdeen, Scotland, Morgan Kaufmann, July 1992.

P 92-10
Hieb, M. R. and Tecuci, G., "Consistency Driven Knowledge Elicitation Within a Learning Oriented Representation of Knowledge," Proceedings of the AAAI-92 Workshop on Knowledge Representation Aspects of Knowledge Acquisition, Los Angeles, CA, July 1992

P 92-11
De Jong, K. A. and Sarma, J., "Generation Gaps Revisited," Proceedings of the Second Workshop on Foundations of Genetic Algorithms, Morgan Kaufmann, July 1992.

P 92-12
De Jong, K. A., "Genetic Algorithms are NOT Function Optimizers," Proceedings of the Second Workshop on Foundations of Genetic Algorithms, Morgan Kaufmann, July 1992.

P 92-13
Michalski, R. S., Kerschberg, L., Kaufman, K. and Ribeiro, J., "Mining For Knowledge in Databases: The INLEN Architecture, Initial Implementation and First Results," Intelligent Information Systems: Integrating Artificial Intelligence and Database Technologies, Vol. 1, No. 1, pp. 85-113, August ,1992.

P 92-14
Kulpa, Z. and Sobolewski, M., "Knowledge-directed Graphical and Natural Language Interface with a Knowledge-based Concurrent Engineering Environment," Proceedings of the 8th International Conference on CAD/CAM, Robotics and Factories of the Future, Metz, France, August 1992.

P 92-15
Bala, J. W., Pachowicz, P. W. and Zhang, J., "Methodology for Iterative Noise-Tolerant Learning and Its Application to Object Recognition in Computer Vision," Proceedings of the 6th International Conference on Systems Research, Informatics and Cybernetics, Baden-Baden, Germany, August 1992.

P 92-16
Hieb, M. R., Mohta, P. and Pachowicz, P. W., "A Learning-Based Incremental Model Evolution for Invariant Object Recognition," Proceedings of the 6th International Conference on Systems Research, Informatics and Cybernetics, Baden-Baden, Germany, August 1992

P 92-17
Tecuci, G., "Automating Knowledge Acquisition as Extending, Updating and Improving a Knowledge Base," IEEE Transactions on Systems, Man, and Cybernetics, Vol. 22, No. 6, pp. 1444-1460, November/December 1992.

P 92-18
Michalski, R. S., "Inferential Theory of Learning: Developing Foundations for Multistrategy Learning," Reports of the Machine Learning and Inference Laboratory, MLI 92-3, George Mason University, Fairfax, VA, September, 1992.

P 92-19
Wnek, J. and Michalski, R. S., "Comparing Symbolic and Subsymbolic Learning: Three Studies," Reports of the Machine Learning and Inference Laboratory, MLI 92-4, George Mason University, Fairfax, VA, September, 1992.

P 92-20
De Jong, K. A., "Are Genetic Algorithms Function Optimizers?," Proceedings of PPSN-92, the 2nd Conference on Parallel Problem Solving from Nature, Brussels, Belgium, Elsevier-Holland, September 1992.

P 92-21
Gomaa, H., Kerschberg, L. and Sugumaran, V., "A Knowledge-Based Approach to Generating Target Systems Specifications from a Domain Model," Proceedings of IFIP World Computer Congress, Madrid, Spain, September 1992.

P 92-22
Vamos, T., "Epistemology, Uncertainty and Social Change," Reports of the Machine Learning and Inference Laboratory, MLI 92-5, George Mason University, Fairfax, VA, October 1992.

P 92-23
Pachowicz, P. W., "A Learning-Based Evolution of Concept Descriptions for an Adaptive Object Recognition," Proceedings of the 4th International Conference on Tools with Artificial Intelligence, Arlington, VA, pp. 316-323, November 1992.

P 92-24
Bala, J. W., Pachowicz, P. W. and Zhang, J., "Iterative Rule Simplification for Noise Tolerant Inductive Learning," Proceedings of the 4th International Conference on Tools with Artificial Intelligence, Arlington, VA, pp. 452-453, November 1992.

P 92-25
De Jong, K. A. and Vafaie, H., "Genetic Algorithms as a Tool for Feature Selection in Machine Learning," Proceedings of the 4th International Conference on Tools with Artificial Intelligence, Arlington, VA, November 1992.

P 92-26
Kerschberg, L. and Seligman, L., "Approximate Knowledge Base/Database Consistency: An Active Database Approach," Proceedings of the First International Conference on Information and Knowledge Management, Baltimore, MD, November 1992.

P 92-27
Kerschberg, L. and Yoon, J. P., "A Framework for Constraint Management in Object-Oriented Databases," Proceedings of the First International Conference on Information and Knowledge Management, Baltimore, MD, November 1992.

P 92-28
Crain, S. and Hamburger, H., "Semantics, Knowledge and NP Modification," Formal Grammar: Theory and Implementation, Oxford, England, Oxford University Press, 1992.

P 92-29
Hamburger, H. and Hashim, R., "Foreign Language Tutoring and Learning Environment," Intelligent Tutoring Systems for Foreign Language Learning, New York & Berlin, Springer Verlag, 1992.

P 92-30
Hamburger, H. and Lodgher, A., "Semantically Constrained Exploration and Heuristic Guidance," Intelligent Instruction by Computer, New York, Taylor and Francis, 1992.

P 92-31
Hamburger, H. and Hashim, R., "Discourse Style and Situation Viewpoint for a Conversational Language Tutor," Proceedings of the International Conference on Computer- Assisted Learning, Wolfville, Nova Scotia, Canada, Springer-Verlag, New York, 1992.

P 92-32
Pan, J. and Hamburger, H., "A Knowledge-based Learning System for Chinese Character Writing," Proceedings of the International Conference on Computer Processing of Chinese and Oriental Languages, Clearwater Beach, FL, December 15-19, 1992.

P 92-33
Hieb, M. R. and Tecuci, G., "Two Methods for Consistency-driven Knowledge Elicitation," Reports of the Machine Learning and Inference Laboratory, MLI 92-6, George Mason University, Fairfax, VA, December 1992.

P 92-34
Arciszewski, T., Bloedorn, E., Michalski, R. S., Mustafa, M. and Wnek, J., "Constructive Induction in Engineering Design," Reports of the Machine Learning and Inference Laboratory, MLI 92-7, George Mason University, Fairfax, VA, December, 1992.

P 92-35
Tecuci, G. and Hieb, M. R., "Consistency-driven Knowledge Elicitation: Using a Machine Learning Oriented Knowledge Representation to Integrate Learning and Knowledge Elicitation in NeoDISCIPLE," Reports of the Machine Learning and Inference Laboratory, MLI 92-8, George Mason University, Fairfax, VA, December 1992.

P 92-36
Arciszewski, T., Dybala, T. and Wnek, J., "A Method for Evaluation of Learning Systems," HEURISTICS, The Journal of Knowledge Engineering, Special Issue on Knowledge Acquisition and Machine Learning, Vol. 5, No. 4, pp. 22-31, 1992.

P 92-37
Hieb, M. R., Mezher, T. M. and Silverman, B. G., "Rule Acquisition for Dynamic Engineering Domains," HEURISTICS, The Journal of Knowledge Engineering, Special Issue on Knowledge Acquisition and Machine Learning, Vol. 5, No. 4, pp. 72-82, 1992.

P 92-38
Wnek, J. and Michalski, R. S., "Experimental Comparison of Symbolic and Subsymbolic Learning," HEURISTICS, The Journal of Knowledge Engineering, Special Issue on Knowledge Acquisition and Machine Learning, Vol. 5, No. 4, pp. 1-21, 1992.

P 92-39
Bala, J. W. and Pachowicz, P. W., "Recognizing Noisy Pattern Via Iterative Optimization and Matching of Their Rule Description," International Journal on Pattern Recognition and Artificial Intelligence, Vol. 6, No. 4, 1992.

P 92-40
Michalski, R. S., "LEARNING = INFERENCING + MEMORIZING: Basic Concepts of Inferential Theory of Learning and Their Use for Classifying Learning Processes," Cognitive Models of Learning, 1992.

P 92-41
Bala, J. W., Bloedorn, E., De Jong, K. A., Kaufman, K., Michalski, R. S., Pachowicz, P. W., Vafaie, H., Wnek, J. and Zhang, J., "A Brief Review of AQ Learning Programs and Their Application to the MONKS Problems," Reports of the Machine Learning and Inference Laboratory,MLI 92-9, George Mason University, Fairfax, VA, 1992.

P 92-42
Michalski, R. S. and Van Mechelen, I., "General Introduction: Purpose, Underlying Ideas, and Scope of the Book," Categories and Concepts: Theoretical Views and Inductive Data Analysis, pp. 1-8, Academic Press, 1993.

1991

P 91-1
Michalski, R. S., "Searching for Knowledge in a World Flooded with Facts ," Applied Stochastic Models and Data Analysis, Vol 7, pp 153-166, 1991.

P 91-2
Bala, J. W. and Pachowicz, P. W., "Application of Symbolic Machine Learning to the Recognition of Texture Concepts," Proceedings of the 7th IEEE Conference on Artificial Intelligence Application, Miami, FL, 1991.

P 91-3
Bala, J. W. and Pachowicz, P. W., "Optimization of Concept Prototypes for the Recognition of Noisy Texture Data," Reports of the Machine Learning and Inference Laboratory, MLI 91-1, School of Information Technology and Engineering, George Mason University, Fairfax, VA, , 1991.

P 91-4
Pachowicz, P. W., "Learning Invariant Texture Characteristics to Dynamic Environments A Model Evolution," Reports of the Machine Learning and Inference Laboratory, MLI 91-2, School of Information Technology and Engineering, George Mason University, Fairfax, VA, 1991.

P 91-5
Tecuci, G., "A Multistrategy Learning Approach to Domain Modeling and Knowledge Acquisition," Proceedings of the European Conference on Machine Learning, Porto, Portugal, Springer-Verlag, 1991.

P 91-6
Tecuci, G. and Michalski, R. S., "Input Understanding as a Basis for Multistrategy Task-adaptive Learning in Ras Zand Zemankova M eds," Proceedings of the International Symposium on Methodologies for Intelligent Systems, Lecture Notes on Artificial Intelligence, Springer-Verlag, 1991.

P 91-7
Michalski, R. S., "Searching for Knowledge in a World Flooded with Facts," an invited talk, Proceedings of the Fifth International Symposium on Applied Stochastic Models and Data Analysis, Granada, Spain, April 23-26 ,1991.

P 91-8
Kerschberg, L. and Weishar, D., "An Intelligent Heterogeneous Autonomous Database Architecture for Semantic Heterogeneity Support," IEEE Workshop on Interoperability in Multidatabase Systems, Kyoto, Japan, April 1991.

P 91-9
Bergadano, F., Matwin, S., Michalski, R. S. and Zhang, J., "Learning Two-tiered Descriptions of Flexible Concepts The POSEIDON System," Reports of the Machine Learning and Inference Laboratory, MLI 91-3, School of Information Technology and Engineering, George Mason University, Fairfax, VA,, May, 1991 .

P 91-10
Wnek, J. and Michalski, R. S., "Hypothesis-Driven Constructive Induction in AQ17 A Method and Experiments," Reports of the Machine Learning and Inference Laboratory, MLI 91-4, School of Information Technology and Engineering, George Mason University, Fairfax, VA, May, 1991.

P 91-11
Tecuci, G. and Michalski, R. S., "A Method for Multistrategy Task-adaptive Learning Based on Plausible Justifications," Machine Learning: Proceedings of the Eighth International Workshop, San Mateo, CA, , Morgan Kaufmann, June, 1991.

P 91-12
Bala, J. W. and Pachowicz, P. W., "Optimization of Concept Prototypes for the Recognition of Noisy Texture Data," Machine Learning Proceedings of the Eighth International Workshop, San Mateo, CA,, Morgan Kaufmann, June 1991.

P 91-13
Michalski, R. S., "Toward a Unified Theory of Learning: An Outline of Basic Ideas," Invited paper, First World Conference on the Fundamentals of Artificial Intelligence, Paris, France, July 1-5, 1991.

P 91-14
Bala, J. W. and Pachowicz, P. W., "Texture Recognition Through Machine Learning and Concept Optimization," Reports of the Machine Learning and Inference Laboratory, MLI 91-5, School of Information Technology and Engineering, George Mason University, Fairfax, VA, July 1991.

P 91-15
Tecuci, G., "Steps Toward Automating Knowledge Acquisition for Expert Systems," Proceedings of the AAAI-91 Workshop on Knowledge Acquisition "From Science To Technology to Tools," , Anaheim, CA, July 1991.

P 91-16
Kaufman, K., Michalski, R. S. and Kerschberg, L., "An Architecture for Integrating Machine Learning and Discovery Programs into a Data Analysis System," Proceedings of the AAAI-91 Workshop on Knowledge Discovery in Databases, Anaheim,CA, July, 1991.

P 91-17
De Jong, K. A. and Spears, W., "An Analysis of Multi-point Crossover," Foundations of Genetic Algorithms, San Mateo, Morgan Kaufmann, July 1991.

P 91-18
De Jong, K. A. and Spears, W., "On the Virtues of Parameterized Uniform Crossover," Proceedings of the 4th International Conference on Genetic Algorithms, Morgan Kaufmann, July, 1991.

P 91-19
Wnek, J. and Michalski, R. S., "Hypothesis-Driven Constructive Induction in AQ17: A Method and Experiments ," Proceedings of the IJCAI-91 Workshop on Evaluating and Changing Representation in Machine Learning, Sydney, Australia, August, 1991.

P 91-20
De Jong, K. A. and Spears, W., "Learning Concept Classification Rules Using Genetic Algorithms," Proceedings of IJCAI-91, Sydney, Australia, Morgan Kaufmann, August 1991.

P 91-21
Kerschberg, L. and Seligman, L., "Federated Knowledge and Database Systems: A New Architecture for Integrating of AI and Database Systems," Proceedings of the IJCAI-91 Workshop on Integrating Artificial Intelligence and Databases, Sydney, Australia, August 1991.

P 91-22
Michalski, R. S., "Beyond Prototypes and Frames: The Two-tiered Concept Representation," Reports of the Machine Learning and Inference Laboratory, MLI 91-6, School of Information Technology and Engineering, George Mason University, September, 1991.

P 91-23
Tecuci, G., "Automating Knowledge Acquisition As Extending, Updating, and Improving A Knowledge Base," Reports of the Machine Learning and Inference Laboratory, MLI 91-7, School of Information Technology and Engineering, George Mason University, Fairfax, VA, September 1991.

P 91-24
Michael, J. B., "Validation, Verification, and Experimentation with Abacus2," Reports of the Machine Learning and Inference Laboratory, MLI 91-8, School of Information Technology and Engineering, George Mason University, Fairfax, VA, September 1991.

P 91-25
Bala, J. W., De Jong, K. A. and Pachowicz, P. W., "Using Genetic Algorithms to Improve the Performance of Classification Rules Produced by Symbolic Inductive Method," Proceedings of the Sixth International Symposium on Methodologies for Intelligent Systems, ISMIS'91, Charlotte, North Carolina, October 16-19, 1991.

P 91-26
Kaufman, K., Michalski, R. S. and Kerschberg, L., "Knowledge Extraction from Databases: Design Principles of the INLEN System," Proceedings of the Sixth International Symposium on Methodologies for Intelligent Systems, ISMIS '91, October 16-19, 1991.

P 91-27
Michalski, R. S., "Inferential Learning Theory: A Conceptual Framework for Characterizing Learning Processes," Reports of the Machine Learning and Inference Laboratory, MLI 91-9, School of Information Technology and Engineering, George Mason University, Fairfax, VA, October, 1991.

P 91-28
Thrun, S. B., Bala, J. W., Bloedorn, E., Bratko, I., Cestnik, B., Cheng, J., De Jong, K. A., Dzeroski, S., Fahlman, S. E., Hamann, R., Kaufman, K., Keller, S., Kononenko, I., Kreuziger, J., Michalski, R. S., Mitchell, T. M., Pachowicz, P., Vafaie, H., Van de Velde, W., Wenzel, W., Wnek, J. and Zhang, J., "The MONK's problems: A Performance Comparison of Different Learning Algorithms," , Carnegie Mellon University, Pittsburgh, PA, October, 1991.

P 91-29
Baum, R. and Kerschberg, L., "A Taxonomy of Knowledge-Based Approaches to Fault Management for Telecommunications Networks," IEEE Conference on Systems, Man and Cybernetics, Charlottesville, VA, October 1991.

P 91-30
Pachowicz, P., "Recognizing and Incrementally Evolving Texture Concepts in Dynamic Environments: An Incremental Model Generalization Approach," Reports of the Machine Learning and Inference Laboratory, MLI 91-10, School of Information Technology and Engineering, George Mason, University, Fairfax, VA, November 1991.

P 91-31
Michalski, R. S. and Tecuci, G. (Eds.), Proceedings of the 1st International Workshop on Multistrategy Learning, MSL-91, Harpers Ferry, WV, 1991.

P 91-32
Michalski, R. S., "Inferential Learning Theory as a Basis for Multistrategy Task-Adaptive Learning ," Proceedings of the First International Workshop on Multistrategy Learning, MSL-91, Harpers Ferry, WV, 3-18, 1991.

P 91-33
Wnek, J. and Michalski, R. S., "An Experimental Comparison of Symbolic and Subsymbolic Learning Paradigms: Phase I -- Learning Logic-Style Concepts," Proceedings of the First International Workshop on Multistrategy Learning, MSL-91, Harpers Ferry, WV, November 7-9, 1991.

P 91-34
Vafaie, H. and De Jong, K. A., "Improving the Performance of a Rule Induction System Using Genetic Algorithm," Proceedings of the First International Workshop on Multistrategy Learning, MSL-91, Harpers Ferry, WV, November 7-9, 1991.

P 91-35
Bala, J. W., De Jong, K. A. and Pachowicz, P., "Integration of Inductive Learning and Genetic Algorithms to Learn Optimal Concept Descriptions from Engineering Data," Proceedings of the First International Workshop on Multistrategy Learning, MSL-91, Harpers Ferry, WV, November 7-9, 1991.

P 91-36
Tecuci, G., "Learning as Understanding the External World," Proceedings of the First International Workshop on Multistrategy Learning, MSL-91, Harpers Ferry, WV, November 7-9, 1991.

P 91-37
Bloedorn, E. and Michalski, R. S., "Data Driven Constructive Induction in AQ17-PRE: A Method and Experiments," Proceedings of the Third International Conference on Tools for AI, San Jose, CA, November 9-14, 1991.

P 91-38
Bala, J. W. and Michalski, R. S., "Learning Textural Concepts Through Multilevel Symbolic Transformations," Proceedings of the Third International Conference on Tools for Artificial Intelligence, San Jose, CA, November 9-14, 1991.

P 91-39
Janssen, T., Bloedorn, E., Hieb, M. R. and Michalski, R. S., "Learning Rules for Preventing and Diagnosing Faults in Large-Scale Data Communications Networks: An Exploratory Study," Proceedings of the Fourth International Symposium on Artificial Intelligence, Cancun, Mexico, November 13-15. 1991.

P 91-40
Pachowicz, P., "Application of Symbolic Inductive Learning to the Acquisitions and Recognition of Noisy Texture Concepts," Applications of Learning and Planning Methods, November 1991.

P 91-41
Bosch, C., Gomaa, H., Kerschberg, L., Sugumaran, V. and Tavakoli, I., "A Prototype Software Engineering Environment for Domain Modeling and Reuse," NASA/Goddard Sixteenth Annual Software Engineering Workshop, December 4-5, 1991.

P 91-42
Kerschberg, L. and Weishar, D., "Data/Knowledge Packets as a Means of Supporting Semantic Heterogeneity in Multidatabase Systems," ACM SIGMOD Record, December 1991.

P 91-43
Kaufman, K., Michalski, R. S. and Kerschberg, L., "Mining for Knowledge in Databases: Goals and General Description of the INLEN System,," Knowledge Discovery in Databases, G. Piatetski-Shapiro and W. J. Frawley (Eds.), Menlo Park, CA , AAAI Press/The MIT Press, 1991.

P 91-44
Hamburger, H. and Maney, T., "Two fold Continuity in Language Learning," Computer-Assisted Language Learning, Vol. 4, No. 2, pp. 8l-92, 1991.

P 91-45
Pachowicz, P., "Local Characteristics of Binary Images and Their Application to the AutomaticControl of Low-Level Robot Vision," Computer Vision, Graphics and Image Processing, Academic Press, 1991.

P 91-46
Thrun, S. B., Bala, J. W., Bloedorn, E., Bratko, I., Cestnik, B., Cheng, J., De Jong, K., Dzeroski, S., Fahlman, S. E., Fisher, D., Hamann, R., Kaufman, K., Keller, S., Kononenko, I., Kreuziger, J., Michalski, R. S., Mitchell, T. M., Pachowicz, P., Reich, Y., Vafaie, H., Van de Velde, W., Wenzel, W., Wnek, J. and Zhang, J., "The MONK's problems: A Performance Comparison of Different Learning Algorithms," Computer Science Reports, CMU-CS-91-197, Carnegie Mellon University (Revised version), Pittsburgh, PA, December, 1991.

P 91-47
Michalski, R. S., Kaufman, K. and Wnek, J., "The AQ Family of Learning Programs: A Review of Recent Developments and an Exemplary Application," Reports of the Machine Learning and Inference Laboratory, MLI 91-11, School of Information Technology and Engineering, George Mason University, Fairfax, VA, December, 1991.

P 91-48
Bloedorn, E. and Michalski, R. S., "Constructive Induction from Data in AQ17-DCI: Further Experiments," Reports of the Machine Learning and Inference Laboratory, MLI 91-12, School of Information Technology and Engineering, George Mason University, Fairfax, VA, December, 1991.

P 91-49
Michalski, R. S., "Concepts as Flexible and context-dependent Sets: the two-tiered view," , George Mason University, Fairfax, VA-22030 , 1991.

P 91-50
Michalski, R. S. and Chilausky, R., "Knowledge Acquisition by Encoding Expert Rules versus Computer Induction from Examples: A Case Study Involving Soybean Pathology," Artificial Intelligence and Software Engineering, pp. 491-520, Alex Publishing Corporation, 1991.

P 91-51
Littman, D. C. and Michalski, R. S., "Future Directions of Artificial Intelligence in a Resource-Limited Environment," Future Directions in Artificial Intelligence, pp. 63-69, North-Holland, 1991.

1990

P 90-1
Michalski, R. S., " Towards a Unified Theory of Learning: Multistrategy Task-adaptive Learning," Reports of the Machine Learning and Inference Laboratory, MLI 90-1, School of Information Technology and Engineering, George Mason University, Fairfax, VA, January, 1990.

P 90-2
Wnek, J., Sarma, J., Wahab, A. and Michalski, R. S., "Comparing Learning Paradigms via Diagrammatic Visualization: A Case Study in Single Concept Learning using Symbolic, Neural Net and Genetic Algorithm Methods," Reports of the Machine Learning and Inference Laboratory, MLI 90-2, School of Information Technology and Engineering, George Mason University, Fairfax, VA, January, 1990.

P 90-3
Wollowski, M., "Learning ICI-Rules through Reporting Differences," Reports of the Machine Learning and Inference Laboratory, MLI 90-3, School of Information Technology and Engineering, George Mason University, Fairfax,VA, January 1990.

P 90-4
Stefanski, P. A., Wnek, J. and Zhang, J., "Bibliography of Recent Machine Learning Research 1985-1989," Reports of the Machine Learning and Inference Laboratory, MLI 90-4, School of Information Technology and Engineering, George Mason University, January, 1990.

P 90-5
Boehm-Davis, D., Dontas, K. and Michalski, R. S., "A Validation and Exploration of Structural Aspects of the Collins-Michalski Theory of Plausible Reasoning," Reports of the Machine Learning and Inference Laboratory, MLI 90-5, School of Information Technology and Engineering, George Mason University, January, 1990.

P 90-6
De Jong, K. A., "Using Neural Networks and Genetic Algorithms as Heuristics for NP-Complete Problems," Proceedings of IJCNN-90, Washington D.C., January, 1990.

P 90-7
De Jong, K. A., "FIS: An AI-based Fault Isolation System," Proceedings of IEEE Southeastern '90, New Orleans, LA, March 1990.

P 90-8
Piotrowski, T., "On Applying Artificial Intelligence Techniques to Building Sea-Going Ships," Reports of the Machine Learning and Inference Laboratory, MLI 90-6, School of Information Technology and Engineering, George Mason University, March 1990.

P 90-9
Freeman, R., "PRODIGY: Its Exploration and Use," Reports of the Machine Learning and Inference Laboratory, MLI 90-7, School of Information Technology and Engineering, George Mason University, May 1990.

P 90-10
Michalski, R. S. and Kodratoff, Y., "Research in Machine Learning; Recent Progress, Classification of Methods and Future Directions," Machine Learning: An Artificial Intelligence Approach, Vol. III, Y. Kodratoff and R. S. Michalski (Eds.), San Mateo, CA, 3-30, Morgan Kaufmann Publishers, June, 1990.

P 90-11
Michalski, R. S., "Learning Flexible Concepts: Fundamental Ideas and a Method Based on Two-tiered Representation," Machine Learning: An Artificial Intelligence Approach, Vol. III, San Mateo, CA, pp. 63-111, Morgan Kaufmann Publishers, June, 1990.

P 90-12
Falkenhainer, B. and Michalski, R. S., "Integrating Quantitative and Qualitative Discovery in the ABACUS System," Machine Learning: An Artificial Intelligence Approach, Vol. III, Y. Kodratoff and R. S. Michalski (Eds.), San Mateo, CA, pp. 153-190, Morgan Kaufmann Publishers, June, 1990.

P 90-13
De Jong, K. A., "Genetic Algorithm Based Learning," Machine Learning: An Artificial Intelligence Approach, Vol. III, San Mateo, CA, pp. 611-638, Morgan Kaufmann Publishers, June 1990.

P 90-14
Kodratoff, Y., "Learning Expert Knowledge by Improving the Explanations Provided by the System," Machine Learning: An Artificial Intelligence Approach, Vol. III, San Mateo, CA, pp. 433-473, Morgan Kaufmann Publishers, June 1990.

P 90-15
Kodratoff, Y. and Tecuci, G., "Apprenticeship Learning in Imperfect Domain Theories," Machine Learning: An Artificial Intelligence Approach, Vol. III, San Mateo, CA, pp. 514-552, Morgan Kaufmann Publishers, June 1990.

P 90-16
Stefanski, P. A., Wnek, J. and Zhang, J., "Bibliography of Recent Machine Learning Research 1985-1989," Machine Learning: An Artificial Intelligence Approach, Vol. III, San Mateo, CA, pp. 685-789, Morgan Kaufmann Publishers, June 1990.

P 90-17
Kodratoff, Y. and Michalski, R. S. (Eds.), Machine Learning: An Artificial Intelligence Approach, Vol. III, San Mateo, CA, Morgan Kaufmann Publishers, June 1990.

P 90-18
De Jong, K. A. and Spears, W., "An Analysis of Multipoint Crossover for Genetic Algorithms," Proceedings of FOCA-90, June 1990.

P 90-19
Pachowicz, P. W., "Integrating Low Level Features Computation with Inductive Learning Techniques for Texture Recognition," International Journal of Pattern Recognition and Artificial Intelligence, Vol. 4, No.2, pp. 147-165, June 1990.

P 90-20
Bala, J. W. and Pachowicz, P. W., "Recognizing Noisy Patterns of Texture Via Iterative Optimization and Matching of Their Rule Description," Reports of the Machine Learning and Inference Laboratory, MLI 90-8, School of Information Technology and Engineering, George Mason University, Fairfax, VA, June 1990.

P 90-21
Pachowicz, P. W., "Learning-Based Architecture for the Robust Recognition of Variable Texture to Navigate in Natural Terrain," Proceedings IEEE International Workshop on Intelligent Robots and Systems, '90, Japan, pp. 135-142, July 1990.

P 90-22
Bala, J. W., "Combining Structural and Statistical Features in a Machine Learning Technique for Texture Classification," Proceedings of the Third International Conference on Industrial and Engineering Applications of AI and Expert Systems, July 1990.

P 90-23
Michalski, R. S., Dontas, K. and Boehm-Davis, D., "Plausible reasoning: An outline of theory and experiments to validate its structural aspects," Reports of the Machine Learning and Inference Laboratory, MLI 90-9, School of Information Technology and Engineering, George Mason University, Fairfax, VA, 1990.

P 90-24
Michael, J. B., Sibley, E. H. and Wexelblat, R. L., "Policy Management, Economics and Risk," Proceedings of the IFAC Second International Conference on Economics and Artificial Intelligence, Paris, France, July 1990.

P 90-25
De Jong, K. A., "Using Genetic Algorithms for Symbolic Learning Tasks," Proceedings of the Conference on the Simulation of Adaptive Behavior, Paris, France, September 1990.

P 90-26
Wechsler, H., Computational Vision, New York, Academic Press, September, 1990.

P 90-27
Bergadano, F., Matwin, S., Michalski, R. S. and Zhang, J., "Learning Two-Tiered Descriptions of Flexible Concepts: The POSEIDON System," Reports of the Machine Learning and Inference Laboratory,MLI 90-10, School of Information Technology and Engineering, George Mason University, Fairfax, VA, September, 1990.

P 90-28
Zhang, J., "Learning Flexible Concepts from Examples: Employing the Ideas of Two-Tiered Concept Representation," Reports of the Machine Learning and Inference Laboratory, MLI 90-11, School of Information Technology and Engineering, George Mason University, Fairfax, VA, September 1990.

P 90-29
De Jong, K. A. and Spears, W. A., "An Analysis of the Interacting Roles of Population Size and Crossover in Genetic Algorithms," Conference on Parallel Problem Solving from Nature, Dortmund, Germany, October 1990.

P 90-30
Wnek, J., Sarma, J., Wahab, A. and Michalski, R. S., "Comparing Learning Paradigms via Diagrammatic Visualization: A Case Study in Concept Learning Using Symbolic, Neural Net and Genetic Algorithm Methods," Proceedings of the 5th International Symposium on Methodologies for Intelligent Systems, ISMIS'90, Knoxville, TN, pp. 428-437, October ,1990.

P 90-31
Michalski, R. S., "A Methodological Framework for Multistrategy Task-adaptive Learning," Proceedings of the 5th International Symposium on Methodologies for Intelligent Systems, ISMIS'90, Knoxville, TN, pp. 404-411, October, 1990.

P 90-32
De Jong, K. A., "Using Genetic Algorithms as a Heuristic for NP-Complete Problems," Proceedings of the ORSA/JIMM Conference, New York, October 1990.

P 90-33
De Jong, K. A. and Spears, W., "Using Genetic Algorithms for Supervised Concept Learning," Proceedings of the Tools for AI Conference, Reston, VA, November 1990.

P 90-34
Bala, J. W. and De Jong, K. A., "Generation of Feature Detectors for Texture Discrimination by Genetic Search," Proceedings of the Tools for AI Conference, Reston, VA, November 1990.

P 90-35
De Jong, K. A. and Dontas, K., "Discovery of Maximal Distance Codes Using Genetic Algorithms," Proceedings of the Tools for AI Conference, Reston, VA, November 1990.

P 90-36
Tecuci, G., "A Multistrategy Learning Approach To Domain Modeling and Knowledge Acquisition," Reports of the Machine Learning and Inference Laboratory, MLI 90-12, School of Information Technology and Engineering, George Mason University, Fairfax, VA, November 1990.

P 90-37
Char, J.M., Cherkassky, V. and Wechsler, H., "Fault-Tolerant Database Using Distributed Associative Memories," Information Sciences, 1990.

P 90-38
"Neural Networks for Visual and Machine Perception," , H. Wechsler (Ed.), Oxford University Press, 1990.

P 90-39
Kaufman, K., Schultz, A. C. and Michalski, R. S., "EMERALD 1: An Integrated System of Machine Learning and Discovery Programs for Education and Research: Programmer's Guide for the Sun Workstation," Reports of the Machine Learning and Inference Laboratory, MLI 90-13, School of Information Technology and Engineering, George Mason University, Fairfax, VA, December, 1990.

P 90-40
Kodratoff, Y., Rouveirol, C., Tecuci, G. and Duval, B., "Symbolic Approaches to Uncertainty," INTELLIGENT SYSTEMS: State of the Art and Future Directions, Z. Ras and M. Zemankova (Eds.), 1990.

P 90-41
Kaufman, K. and Michalski, R. S., "EMERALD 1: An Integrated System of Machine Learning and Discovery Programs for Education and Research: Programmer's Guide for the VaxStation," Reports of the Machine Learning and Inference Laboratory, MLI 90-14, School of Information Technology and Engineering, George Mason University, Fairfax, VA, December, 1990.

P 90-42
Michalski, R. S., "Multistrategy Constructive Learning: Toward a Unified Learning Theory," invited paper at the ONR Knowledge Acquisition Workshop, Crystal City, VA, November 6-7 1990.

P 90-43
Michalski, R. S., "A Theory and Methodology of Inductive Learning," Readings in Machine Learning, J. Shavlik and T. G. Dietterich (Eds.), Morgan Kaufmann, 1990.

P 90-44
Boehm-Davis, D., Dontas, K. and Michalski, R. S., "Plausible reasoning: An outline of theory and experiments to validate its structural Properties," Proceedings of the Fourth International Symposium on Methodologies for Intelligent Systems, Charlotte, North Carolina, pp. 260-272, North Holland, 1990.

1989

P 89-1
Kodratoff, Y., "Characterizing Machine Learning Programs: A European Compilation," Reports of the Machine Learning and Inference Laboratory, MLI 89-1, School of Information Technology and Engineering, George Mason University, Fairfax, VA, February 1989.

P 89-2
Stefanski, P. A. and Wnek, J., "Bibliography Maintenance System," Reports of the Machine Learning and Inference Laboratory, MLI 89-2, School of Information Technology and Engineering, George Mason University, Fairfax, VA, March 1989.

P 89-3
Carpineto, C., "Inductive Refinement of Causal Theories," Reports of the Machine Learning and Inference Laboratory, MLI 89-3, School of Information Technology and Engineering, George Mason University, Fairfax, VA, March 1989.

P 89-4
Mozetic, I., "Hierarchical Model-Based Diagnosis," Reports of the Machine Learning and Inference Laboratory, MLI 89-4, School of Information Technology and Engineering, George Mason University, Fairfax, VA

P 89-5
Pachowicz, P. W., "Comparison of Small Autonomous Robots by the Analysis of Their Functional Components," Reports of the Machine Learning and Inference Laboratory, MLI 89-5, School of Information Technology and Engineering, George Mason University, Fairfax, VA, 1989.

P 89-6
Swangwanna, S. and Zytkow, J. M., "Real-Time Decision Making for Autonomous Flight Control," SAE Technical Paper Series, 891053, General Aviation Aircraft Meeting & Exposition, Wichita, Kansas, pp. 1-7, April 1989.

P 89-7
De Jong, K. A. and Spears, W. A., "Using Genetic Algorithms to Solve NP-Complete Problems," Proceedings of the Third International Conference on Genetic Algorithms and their Applications , George Mason University, Fairfax, VA, pp. 124-132, June 1989.

P 89-8
Kelly, Jr., J. D., "PRS: A System for Plausible Reasoning," M.S. Thesis, University of Illinois, Urbana-Champaign, 1989.

P 89-9
Zhang, J. and Michalski, R. S., "A Description of Preference Criterion in Constructive Learning: A Discussion of Basic Issues," Proceedings of the 6th International Workshop on Machine Learning, Cornell University, Ithaca, NY, pp. 17-19, Morgan Kaufmann, June 1989.

P 89-10
Tecuci, G. and Kodratoff, Y., "Multi-strategy Learning in Non-homogeneous Domain Theories," Proceedings of the 6th International Workshop on Machine Learning, A. Segre (Ed.), Cornell University, Ithaca, NY , pp. 14-16, Morgan Kaufmann, June 1989.

P 89-11
Erkmen, A. M. and Stephanou, H. E., "Shape and Curvature Data Fusion by Conductivity Analysis," NATO ARW Multisensor Fusion for Computer Vision, Grenoble, France, June 1989.

P 89-12
Wechsler, H. and Zimmerman, G. L., "Distributed Associative Memory (DAM) for Bin-Picking," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 11, No. 8, pp. 814-822, August 1989.

P 89-13
Kaufman, K., Michalski, R. S. and Kerschberg, L., "Mining for Knowledge in Databases: Goals and General Description of the INLEN System," Proceedings of IJCAI-89 Workshop on Knowledge Discovery in Databases, Detroit, MI, August 1989.

P 89-14
Michalski, R. S. and Littman, D. C., "Future Directions of AI in a Resource-Limited Environment," Proceedings of IJCAI-89 Workshop on Knowledge Discovery in Databases, Detroit, MI, August 1989.

P 89-15
Stephanou, H. E. and Yegenoglu, F., "Collision-Free Path Planning for Multi-robot Systems," Proceedings of the IEEE International Symposium on Intelligent Control, Albany, NY, September 1989.

P 89-16
Bergadano, F., Matwin, S., Michalski, R. S. and Zhang, J., "Learning Flexible Concepts Through a Search for Simpler but Still Accurate Descriptions," Proceedings of the Fourth AAAI-Sponsored Knowledge Acquisition for Knowledge-Based Systems Workshop, Banff, Canada, pp. 1-10, October 1989.

P 89-17
Boehm-Davis, D., Dontas, K. and Michalski, R. S., "Plausible Reasoning: An Outline of Theory and Experiments," Proceedings of the Fourth International Symposium on Methodologies for Intelligent Systems, Charlotte, NC, pp. 260-272, October 12-14, 1989.

P 89-18
Pachowicz, P. W., "Low-Level Numerical Characteristics and Inductive Learning Methodology in Texture Recognition," Proceedings of the IEEE International Workshop on Tools for Artificial Intelligence, Fairfax, VA, pp. 91-98, October, 1989.

P 89-19
Stefanski, P. A. and Zytkow, J. M., "A Multisearch Approach to Sequence Prediction," Proceedings of the Fourth International Symposium on Methodologies for Intelligent Systems, Charlotte, NC, pp. 359-366, October 1989.

P 89-20
Michalski, R. S., "Multistrategy Constructive Learning: Toward a Unified Theory of Learning," Proceedings of ONR Workshop on Knowledge Acquisition, Arlington, VA, November 1989.

P 89-21
Pachowicz, P. W. and Zytkow, J. A., "Fusion of Vision and Touch for Spatio-temporal Reasoning in Learning Manipulation Tasks," SPIE Symposium on Intelligent Robotics Systems, Philadelphia, PA, November 1989.

P 89-22
Michalski, R. S. and Zhang, J., "Rule Optimization Via SG-TRUNC Method," Proceedings of the Fourth European Working Session on Learning, December 1989.

P 89-23
Collins, A. and Michalski, R. S., "The Logic of Plausible Reasoning: A Core Theory," Cognitive Science, Vol. 13, pp. 1-49, 1989.

P 89-24
De Jong, K. A., "An Artificial Intelligence Approach to Analog Systems Diagnosis," Testing and Diagnosis of Analog Systems, R-W. Liu (Ed.), Van Nostrand-Reinhold, 1991.

P 89-25
Baskin, A. B. and Michalski, R. S., "An Integrated Approach to the Construction of Knowledge-Based Systems: Experience with ADVISE and Related Programs," Topics in Expert System Design, G. Guida and C. Tasso (Eds.), pp. 111-143, New York: North-Holland, 1989.

P 89-26
Kaufman, K., Michalski, R. S., Zytkow, J. M. and Kerschberg, L., "The INLEN System for Extracting Knowledge from Databases: Goals and General Description," Reports of the Machine Learning and Inference Laboratory, MLI 89-6, School of Information Technology and Engineering, George Mason University, Fairfax, VA, 1989.

P 89-27
Kaufman, K., Michalski, R. S. and Schultz, A. C., "EMERALD 1: An Integrated System of Machine Learning and Discovery Programs for Education and Research, User's Guide," Reports of the Machine Learning and Inference Laboratory, MLI 89-7, School of Information Technology and Engineering, George Mason University, Fairfax, VA, 1989.

P 89-28
Fermanian, T., Katz, B., Kelly, Jr., J. D. and Michalski, R. S., "AGASSISTANT: An Artificial Intelligence System for Discovering Patterns in Agricultural Knowledge and Creating Diagnostic Advisory Systems," Agronomy Journal, Vol. 81,No. 2, pp. 306-312, 1989.

P 89-29
Fermanian, T. and Michalski, R. S., "WEEDER: An Advisory System for the Identification of Grasses in Turf," Agronomy Journal, Vol. 81, No. 2, pp. 313-316, 1989.

P 89-30
Michalski, R. S., "Two-Tiered Concept Meaning, Inferential Matching and Conceptual Cohesiveness," Similarity and Analogical Reasoning, S. Vosniadou and A. Ortony (Eds.), New York: Cambridge University Press, 1989.

P 89-31
Ko, H., "Empirical Assembly Planning: A Learning Approach," Reports of the Machine Learning and Inference Laboratory, MLI 89-8, School of Information Technology and Engineering, George Mason University, Fairfax, VA, 1989.

P 89-32
Kodratoff, Y. and Tecuci, G., "The Central Role of Explanations in DISCIPLE," Knowledge Representation Organization in Machine Learning, K. Morik (Ed.), Berlin, pp. 135-147, Springer Verlag, 1989.

P 89-33
Nguyen, T. N. and Stephanou, H. E., "A Continuous Model of Robot Hand Preshaping," Proceedings of IEEE International Conference on Systems, Man and Cybernetics, Boston, MA, November 1989.

P 89-34
Erkmen, A. M. and Stephanou, H. E., "Preshape Jacobians for Minimum Momentum Grasping," Proceedings of IEEE International Conference on Systems, Man and Cybernetics, Boston, MA, November 1989.

P 89-35
Erkmen, A. M. and Stephanou, H. E., "Multiresolutional Sensor Fusion by Conductivity Analysis," Proceedings of SPiE Symposium on Advances in Intelligent Robotics Systems, Philadelphia, PA, November 1989.

P 89-36
Ko, H. and Michalski, R. S., "Types of Explanation and Their Role in Multistrategy Constructive Learning," Reports of the Machine Learning and Inference Laboratory, School of Information Technology and Engineering, George Mason University, Fairfax, VA, 1989.

1988

P 88-1
Michalski, R. S. and Watanabe, L., "Constructive Closed-Loop Learning: Fundamental Ideas and Examples," Reports of the Machine Learning and Inference Laboratory, MLI 88-1, School of Information Technology and Engineering, George Mason University, Fairfax, VA, 1988.

P 88-2
Ko, H. and Michalski, R. S., "Types of Explanation and Their Role in Constructive Closed-loop Learning," Reports of the Machine Learning and Inference Laboratory, MLI 88-2, School of Information Technology and Engineering, George Mason University, Fairfax, 1988.

P 88-3
Lavrac, N. and Mozetic, I., "Incremental Learning from Examples in a Logic-Based Formalism," Proceedings of Machine Learning, Meta-Reasoning and Logic Workshop, Sesimbra, Portugal, February 1988.

P 88-4
Michalski, R. S. and Ko, H., "On the Nature of Explanation or Why Did the Wine Bottle Shatter," Proceedings of the Spring Symposium Series: Explanation-Based Learning, Stanford University, pp. 12-21, March 1988.

P 88-5
Char, J.M., Cherkassky, V., Wechsler, H. and Zimmerman, G. L., "Distributed and Fault-Tolerant Computation for Retrieval Tasks Using Distributed Associative Memories," IEEE Transactions on Computers, Vol. 37, No. 4, pp. 484-490, April 1988.

P 88-6
Ko, H., "Empirical Assembly Planning: A Learning Approach," Ph.D. Dissertation, University of Illinois, Urbana-Champaign, May 1988.

P 88-7
Holder, L. B., Stepp, R. and Whitehall, B. L., "Toward Intelligent Machine Learning Algorithms," Reports of Coordinated Science Laboratory, UILU-ENG-88-2221, College of Engineering, University of Illinois, Urbana-Champaign, May 1988.

P 88-8
Holder, L. B., "Discovering Substructure In Examples," Reports of Coordinated Science Laboratory, UILU-ENG-88-2223, College of Engineering, University of Illinois, Urbana-Champaign, May 1988.

P 88-9
Stepp, R., "Machine Learning from Structured Objects," Reports of Coordinated Science Laboratory, niversity of Illinois, Urbana-Champaign, pp. 353-363, May 1988.

P 88-10
Holder, L. B., "Substructure Discovery in SUBDUE," Reports of Coordinated Science Laboratory, UILU-ENG-88-2220, College of Engineering, University of Illinois, Urbana-Champaign, May 1988.

P 88-11
Whitehall, B. L., "Substructure Discovery of Macro-Operators," Reports of Coordinated Science Laboratory, UILU-ENG-88-2219, College of Engineering, University of Illinois, Urbana-Champaign, May 1988.

P 88-12
Nowicki, A. R., "A Methodology for Representing Natural Language Expressions in Variable-Valued Logic," Reports of the Machine Learning and Inference Laboratory, MLI 88-3, School of Information Technology and Engineering, George Mason University, Fairfax, VA, June 1988.

P 88-13
Greene, G. H., "The Abacus.2 System for Quantitative Discovery: Using Dependencies to Discover Non-Linear Terms," Reports of the Machine Learning and Inference Laboratory, MLI 88-4, School of Information Technology and Engineering, George Mason University, Fairfax, VA, June 1988.

P 88-14
De Jong, K. A. and Schultz, A. C., "Using Experience-Based Learning in Game Playing," Proceedings of the Fifth International Conference on Machine Learning, Ann Arbor, MI, Oxford, pp. 284-290, Clarendon Press, June 1988.

P 88-15
Dontas, K., "APPLAUSE: An Implementation of the Collins-Michalski Theory of Plausible Reasoning," M.S. Thesis, Computer Science Department, University of Tennessee, Knoxville, TN, August 1988.

P 88-16
Bergadano, F., Matwin, S., Michalski, R. S. and Zhang, J., "A General Criterion for Measuring Quality of Concept Descriptions," Reports of the Machine Learning and Inference Laboratory, MLI 88-5, School of Information Technology and Engineering, George Mason University, Fairfax, VA, October 1988.

P 88-17
Bergadano, F., Matwin, S., Michalski, R. S. and Zhang, J., "Measuring Quality of Concept Descriptions," Proceedings of the Third European Working Session on Learning, Glasgow, pp. 1-14, October 1988.

P 88-18
Bergadano, F., Matwin, S., Michalski, R. S. and Zhang, J., "Representing and Acquiring Imprecise and Context-Dependent Concepts in Knowledge-based Systems," Proceedings of the 3rd International Symposium on Methodologies for Intelligent Systems, Turin, Italy, pp. 270-280, October 1988.

P 88-19
Bergadano, F., Matwin, S., Michalski, R. S. and Zhang, J., "Learning Two-Tiered Descriptions of Flexible Concepts: A Method Employing Examples of Varied Typicality and A Two-staged Construction of the Base Concept Representation Part I: Principles and Methodology," Reports of the Machine Learning and Inference Laboratory, MLI-88-6, School of Information Technology and Engineering, George Mason University, Fairfax, VA, November 1988.

P 88-20
Bergadano, F., Matwin, S., Michalski, R. S. and Zhang, J., "Learning Two-Tiered Descriptions of Flexible Concepts: A Method Employing Examples of Varied Typicality and A Two-staged Construction of the Base Concept Representation Part II: Algorithms and Experiments," Reports of the Machine Learning and Inference Laboratory,MLI-88-7, School of Information Technology and Engineering, George Mason University, MLI 88-6, Fairfax, VA, November 1988.

P 88-21
Collins, A. and Michalski, R. S., "The Logic of Plausible Reasoning: A Core Theory," Reports of the Machine Learning and Inference Laboratory, MLI 88-8, School of Information Technology and Engineering, George Mason University, Fairfax, VA, November 1988.

P 88-22
Wechsler, H. and Zimmerman, G. L., "2-D Invariant Object Recognition Using Distributed Associative Memories," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 10, No. 6, pp. 811-821, November 1988.

P 88-23
Stefanski, P. A., "An Introduction to the Computer Facilities of the GMU Center for Artificial Intelligence," Reports of the Machine Learning and Inference Laboratory, MLI 88-9, School of Information Technology and Engineering, George Mason University, Fairfax, VA, November 1988.

P 88-24
Reinke, R. and Michalski, R. S., "Incremental Learning of Concept Descriptions: A Method and Experimental Results," Machine Intelligence II, J. E. Hayes, D. Michie and J. Richards (Eds.), pp. 263-288, Oxford: Clarendon Press, 1988.

P 88-25
Sinclair, J. B. and Michalski, R. S., "Computer-Based Consulting System For Diagnosing Soybean Diseases," , Depts. of Plant Pathology and Computer Science, University of Illinois, Urbana-Champaign, 1988.

P 88-26
Wechsler, H. and Zimmerman, G. L., "Distributed Associative Memories and Data Fusion," Proceedings of the IEEE Second International Conference on Neural Networks, Boston, MA, November, 1988.

P 88-27
Channic, T. D., "TEXPERT: An Application of Machine Learning to Texture Recognition," M.S. Thesis, University of Illinois, Urbana-Champaign, 1988.

P 88-28
Carbonell, T. J., Michalski, R. S. and Mitchell, T. M., "Machine Learning: A Historical and Methodological Analysis," Readings from AI Magazine, R. Engelmore (Ed.), Vols. 1-5,1980-1985, Menlo Park, CA, pp. 400-408, American Association for Artificial Intelligence, 1988.

P 88-29
Bratko, I., Lavrac, N. and Mozetic, I., "Automatic Synthesis and Compression of Cardiological Knowledge," Machine Intelligence II, pp. 435-454, Oxford: Clarendon Press, 1988.

P 88-30
De Jong, K. A., Marrone, M., Pipitone, F. and Spears, W., "The FIS Electronics Troubleshooting Project," Expert Systems Applications to Telecommunications, pp. 73-101, Wiley and Sons, 1988.

P 88-31
De Jong, K. A., "Learning with Genetic Algorithms: An Overview," Machine Learning, Vol. 3, pp. 121-138, 1988.

P 88-32
Michalski, R. S., "On the Nature of Learning: Problems and Research Directions," Informatyka Part 1, No. 2 and Informatyka Part 3, No. 3, (Translators: E. Pierzchala and P. Zielczynski), (translation of this 1986 Book Chapter), 1988.

P 88-33
Medin, D. L., Michalski, R. S. and Wattenmaker, W. D., "Constraints and Preferences in Inductive Learning: An Experimental Study Comparing Human and Machine Performance," Cognitive Science, 1987.

P 88-34
Antsaklis, P. J., De Jong, K. A., Meyrowitz, A. L., Meystel, A., Michalski, R. S. and Sutton, R. S., "Machine Learning in a Dynamic World: Panel Discussion," Proceedings of the IEEE International Symposium on Intelligent Control, Arlington, VA, August 24-26, 1988.

P 88-35
Subutai, A., " Machine Learning as a tool for analysis in social sciences," , Department of Computer Science, University of Illinois at Urbana-Champaign, 1988.

1987

P 87-1
Michalski, R. S., Baskin, A. B., Uhrik, C. T. and Channic, T. D., "The ADVISE.1 Meta-Expert System: The General Design and a Technical Description," Reports of the Intelligent Systems Group, ISG 86-8, UIUCDCS-F-87-962, Department of Computer Science, University of Illinois, Urbana-Champaign, January 1987.

P 87-2
Bentrup, J. A., Mehler, G. J. and Riedesel, J. D., "IINDUCE 4: A Program for Incrementally Learning Structural Descriptions from Examples," Reports of the Intelligent Systems Group, ISG 87-2, UIUCDCS-F-87-958, Department of Computer Science, University of Illinois, Urbana-Champaign, February,1987.

P 87-3
Baskin, A. B. and Stepp, R., "The Role of Deterministic and Non-Deterministic Rule Scheduling in Expert Systems," Sixth National Conference on Artificial Intelligence, AAAI, 1987.

P 87-4
Katz, B., Fermanian, T. and Michalski, R. S., "AgAssistant: An Experimental Expert System Builder for Agricultural Applications," Reports of the Intelligent Systems Group, ISG 87-16, UIUCDCS-F-87-978, Department of Computer Science, University of Illinois, Urbana-Champaign, October 1987.

P 87-5
Michalski, R. S., Ko, H. and Chen, K., "Qualitative Prediction: the SPARC/G Methodology for Inductively Describing and Predicting Discrete Processes," Current Issues in Expert Systems, A. Van Lamsweerde and P. Dufour (Eds.), London, pp. 125-158, Academic Press Inc., 1987.

P 87-6
Michalski, R. S., "Learning Strategies and Automated Knowledge Acquisition: An Overview," Computational Models of Learning: Symbolic Computation, L. Bolc and G. L. Bradshaw (Eds.), pp. 1-19, New York: Springer-Verlag, 1987.

P 87-7
Whitehall, B. L., "Substructure Discovery in Executed Action Sequences," Reports of the Intelligent Systems Group, UILU-ENG-87-2256, Department of Computer Sciences, University of Illinois, Urbana-Champaign, September 1987.

P 87-8
Wechsler, H. and Zimmerman, G. L., "Fault-Tolerant Recognition Using DAM's," Proceedings of the IEEE First International Conference on Neural Networks, Vol. II, San Diego, CA, pp. 719-726, June 21-24,1987.

P 87-9
De Jong, K., "On Using Genetic Algorithms to Search Program Spaces," Proceedings of the Second International Conference on Genetic Algorithms, Cambridge, MA, pp. 210-216, July 28-31, 1987.

P 87-10
Michalski, R. S., Carbonell, T. J. and Mitchell, T. M. (Eds.), Machine Learning: An Artificial Intelligence Approach, Vol. I-II, Japanese translation, Kyoritsu Publishing Company, 1987.

P 87-11
Medin, D. L., Michalski, R. S. and Wattenmaker, W. D., "Constraints and Preferences in Inductive Learning: An Experimental Study of Human and Machine Performance," Cognitive Science, Vol. 11, pp. 299-339, 1987.

1986

P 86-1
Medin, D. L., Wattenmaker, W. D. and Michalski, R. S., "Constraints and Preferences in Inductive Learning: An Experimental Study Comparing Human and Machine Performance," Reports of the Intelligent Systems Group, ISG 86-1, UIUCDCS-F-86-952, Department of Computer Science, University of Illinois, Urbana, February 1986.

P 86-2
Goldfain, M., "A Translation System from Clausal Form into Annotated Predicate Calculus," Reports of the Intelligent Systems Group, ISG 86-2, UIUCDCS-F-86-954, Department of Computer Science, University of Illinois, Urbana, February 1986.

P 86-3
Collins, A. and Michalski, R. S., "The Logic of Plausible Reasoning: An Advanced Report," Reports of the Intelligent Systems Group, ISG 86-3, UIUCDCS-F-86-951, Department of Computer Science, University of Illinois, Urbana, February 1986.

P 86-4
Chen, K., Ko, H. and Michalski, R. S., "Qualitative Prediction: The SPARC/G Methodology for Inductively Describing and Predicting Discrete Processes," Reports of the Intelligent Systems Group, ISG 86-4, UIUCDCS-F-86-942, Department of Computer Science, University of Illinois, Urbana, 1986.

P 86-5
Hong, J., Mozetic, I. and Michalski, R. S., "AQ15: Incremental Learning of Attribute-Based Descriptions from Examples, The Method and User's Guide," Reports of the Intelligent Systems Group, ISG 86-5, UIUCDCS-F-86-949, Department of Computer Science, University of Illinois, Urbana, May 1986.

P 86-6
Michalski, R. S., "Machine Learning Research in the Artificial Intelligence Laboratory at Illinois," Machine Learning: A Guide to Current Research, T. M. Mitchell, T. J. Carbonell and R. S. Michalski (Eds.), Kluwer Publishing Company, 1986.

P 86-7
Ko, H. and Lee, L., "Toward a Practical Planning System for Assembly Task," Reports of the Intelligent Systems Group, ISG 86-7, UIUCDCS-F-86-957, Department of Computer Science, University of Illinois Urbana, 1986.

P 86-8
Baskin, A. B., Borodkin, S., Boulanger, A., Channic, T. D., Michalski, R. S., Reinke, R., Rodewald, L. E. and Uhrik, C. T., "A Technical Description of the ADVISE.1 Meta-Expert System that Integrates Multiple Knowledge Representations and Learning Capabilities," Reports of the Intelligent Systems Group, ISG 86-8, UIUCDCS-F-86-962, Department of Computer Science, University of Illinois, Urbana, March 6, 1986.

P 86-9
Hoff, W., Michalski, R. S. and Stepp, R., "INDUCE.3: A Program for Learning Structural Descriptions from Examples," Reports of the Intelligent Systems Group, ISG 86-9, UIUCDCS-F-86-960, Department of Computer Science, University of Illinois, Urbana, 1986.

P 86-10
Iwanska, L., "Critical Issues in Natural Language Understanding and their Importance to Machine Learning," Reports of the Intelligent Systems Group, ISG 86-10, UIUCDCS-F-86-953, Department of Computer Science, University of Illinois, Urbana, 1986.

P 86-11
Haddawy, P., "A Variable Precision Logic Inference System Employing the Dempster-Shafer Uncertainty Calculus," Reports of the Intelligent Systems Group, ISG 86-11, UIUCDCS-F-86-959, Department of Computer Science, University of Illinois, Urbana, 1986.

P 86-12
Chen, K., "Smooth Path Tracking through Symbolic Computations," Reports of the Intelligent Systems Group," , ISG 86-13, UIUCDCS-F-86-963, Department of Computer Science, University of Illinois, Urbana, 1986.

P 86-13
Chen, K., "The Inductive Acquisition of Temporal Knowledge," Reports of the Intelligent Systems Group, ISG 86-14, UIUCDCS-F-86-964, Department of Computer Science, University of Illinois, Urbana , 1986.

P 86-14
Thornburg, G., "Where Expert Systems Intersect with Information Retrieval: Issues and Applications," Reports of the Intelligent Systems Group, ISG-86-15, UIUCDCS-F-86-956, Department of Computer Science, University of Illinois, Urbana, 1986.

P 86-15
Michalski, R. S., "Dynamic Recognition: An Outline of Theory of How to Recognize Concepts without Matching Rules," Reports of the Intelligent Systems Group, ISG 86-16, UIUCDCS-F-86-965, Urbana, 1986.

P 86-16
Hong, J., Michalski, R. S. and Uhrik, C. T., "An Extension Matrix Approach to the General Covering Problem," SPIE Applications of Artificial Intelligence III, Vol. 635, 1986.

P 86-17
Michalski, R. S., "Concept Learning," AI Encyclopedia, January 1986.

P 86-18
Michalski, R. S. and Stepp, R., "Clustering," AI Encyclopedia, January 1986.

P 86-19
Stepp, R. and Michalski, R. S., "Conceptual Clustering of Structured Objects: A Goal-Oriented Approach," AI Journal, 1986.

P 86-20
Falkenhainer, B. and Michalski, R. S., "Integrating Quantitative and Qualitative Discovery: The ABACUS System," Reports of the Intelligent Systems Group, ISG-86-17, UIUCDCS-F-86-967, University of Illinois, Urbana, May, 1986.

P 86-21
Skorstad, G. and Skorstad, J. C., "Parallel Concept Learning on the Connection Machine," Reports of the Intelligent Systems Group, ISG 86-18, UIUCDCS-F-86-966, University of Illinois, Urbana, July, 1986.

P 86-22
Fermanian, T., Michalski, R. S. and Katz, B., "Applications of Artificial Intelligence to Agricultural Problems," International Congress on Computers in Biotechnology Abstracts, Baltimore Convention Center, Maryland, January 30-31, 1986.

P 86-23
Michalski, R. S., Mozetic, I., Hong, J. and Lavrac, N., "The AQ15 Inductive Learning System: An Overview and Experiments," Reports of the Intelligent Systems Group, ISG 86-20, UIUCDCS-R-86-1260, Department of Computer Science, University of Illinois, Urbana, 1986.

P 86-24
Michalski, R. S., "Two-Tiered Concept Meaning, Inferential Matching and Conceptual Cohesiveness," Invited paper for the Allerton Conference on Analogy and Similarity , ISG 86-21, UIUCDCS-F-86-968, University of Illinois, Urbana, IL, June 12-14, 1986.

P 86-25
Uhrik, C. T., "A Rule Exerciser for Knowledge Base Enhancement in Expert Systems," Reports of the Intelligent Systems Group, ISG 86-23, UIUCDCS-F-86-969, M.S. Thesis, Department of Computer Science, University of Illinois, Urbana, IL, September 1986.

P 86-26
Michalski, R. S., Mozetic, I., Hong, J. and Lavrac, N., "The Multi-Purpose Incremental Learning System AQ15 and its Testing Application to Three Medical Domains," Proceedings of the National Conference on Artificial Intelligence, AAAI, Philadelphia, August 11-15, 1986.

P 86-27
Ko, H., "Controlling Attention in Inference Machine," Technical Report, University of Illinois, Urbana, IL, 1986.

P 86-28
Michalski, R. S., "Understanding the Nature of Learning: Issues and Research Directions," Machine Learning: An Artificial Intelligence Approach , Vol. II, pp. 1-25, Morgan-Kaufmann Publishers, 1986.

P 86-29
Michalski, R. S. and Winston, P. H., "Variable Precision Logic," Artificial Intelligence Journal 29 , pp. 121-146, Elsevier Science Publishers B.V. (North-Holland), 1986.

P 86-30
Stepp, R. and Michalski, R. S., "Conceptual Clustering: Inventing Goal-Oriented Classifications of Structured Objects," chapter in Machine Learning: An Artificial Intelligence Approach, R. S. Michalski, T. J. Carbonell and T. M. Mitchell (Eds.), Vol. II, Morgan-Kaufmann Publishers, 1986.

P 86-31
De Jong, K., "Fault Isolation Systems," Proceedings of the IEEE Symposium on VLSI Design, Atlantic City, NJ, March, 1986 .

P 86-32
De Jong, K., "Knowledge Acquisition for Fault Isolation Systems," Proceedings of the Workshop on Knowledge Acquisition for Knowledge-Based Systems, Banff, Canada, October, 1986.

P 86-33
Michalski, R. S., Ko, H. and Chen, K., "Qualitative Prediction: The SPARC/G Methodology for Inductively Describing and Predicting Discrete Processes," chapter in Expert Systems, Academic Press Inc., London, 1986.

P 86-34
Machine Learning: An Artificial Intelligence Approach, Vol. II, Los Altos, CA, Morgan Kaufmann Publishers, Inc., 1986.

P 86-35
Mitchell, T. M., Carbonell, T. J. and Michalski, R. S. (Eds.), Machine Learning: Guide to Current Research, Kluwer Publishing Co., 1986.

P 86-36
Michalski, R. S., Amarel, S., Lenat, D., Michie, D. and Winston, P. H., "Machine Learning: Challenges of the 80's, (Edited transcripts of a panel discussion)," Machine Learning: An Artificial Intelligence Approach Vol. II, R. S. Michalski, T. J. Carbonell and T. M. Mitchell (Eds.), Los Altos, CA, pp. 27-41, Morgan Kaufmann Publishers, 1986.

1985

P 85-1
Becker, J., "AQ-PROLOG: A Prolog Implementation of an Attribute-Based Inductive Learning System," Reports of the Intelligent Systems Group, ISG 85-1, UIUCDCS-F-85-930, Department of Computer Science, University of Illinois, Urbana, January 1985.

P 85-2
Rendell, L., "Substantial Constructive Induction Using Layered Information Compression: Tractable Feature Formation in Search," UIUCDCS-R-85-1198, Department of Computer Science, University of Illinois, Urbana

P 85-3
Hoffman, P., "MEL - A Learning Program that Improves by Experience in Playing the Game of MILL," Reports of the Intelligent Systems Group, ISG 85-2, UIUCDCS-F-85-931, Department of Computer Science, University of Illinois, Urbana, January 1985.

P 85-4
Newkirk, P., "TURF: An Expert System for Ground Development," Reports of the Intelligent Systems Group, ISG 85-3, UIUCDCS-F-85-933, Department of Computer Science, University of Illinois, Urbana, January 1985.

P 85-5
Channic, T. D., "Editing Network-Structured Knowledge Bases in the ADVISE System," Reports of the Intelligent Systems Group, ISG 85-4, UIUCDCS-F-85-934, Department of Computer Science, University of Illinois, Urbana, February 1985.

P 85-6
Becker, J., "Topics in Incremental Learning of Discriminant Descriptions," Reports of the Intelligent Systems Group, ISG 85-5, UIUCDCS-F-85-935, Department of Computer Science, University of Illinois,Urbana, February 1985.

P 85-7
Becker, J., "Word Sense Disambiguation Using Constraints and Supports," Reports of the Intelligent Systems Group, ISG 85-6, UIUCDCS-F-85-936, Department of Computer Science, University of Illinois,Urbana, February 1985.

P 85-8
Becker, J., "Macros and Utilities for Franz Lisp," Reports of the Intelligent Systems Group, ISG 85-7, UIUCDCS-F-85-937, Department of Computer Science, University of Illinois,Urbana, February 1985.

P 85-9
Michalski, R. S., "Understanding the Nature of Learning: Issues and Research Directions," Reports of the Intelligent Systems Group, ISG 85-8, UIUCDCS-F-85-938, Department of Computer Science, University of Illinois, Urbana, February 1985.

P 85-10
Dietterich, T. G. and Michalski, R. S., "Discovering Patterns in Sequence of Events," Artificial Intelligence Journal, Vol. 25, No 2, pp. 187-232, 1985.

P 85-11
Dietterich, T. G. and Michalski, R. S., "Learning to Predict Sequences," Reports of the Intelligent Systems Group, ISG 85-9, UIUCDCS-F-85-939, Department of Computer Science, University of Illinois, Urbana, February 1985.

P 85-12
Stepp, R. and Michalski, R. S., "Conceptual Clustering: Inventing Goal-Oriented Classifications of Structured Objects," Reports of the Intelligent Systems Group, ISG 85-10, UIUCDCS-F-85-940, Department of Computer Science, University of Illinois, Urbana, February 1985.

P 85-13
Michalski, R. S., Ko, H. and Chen, K., "SPARC/E(V.2), An Eleusis Rule Generator and Game Player," Reports of the Intelligent Systems Group, ISG 85-11, UIUCDCS-F-85-941, Department of Computer Science, University of Illinois, February 1985.

P 85-14
Mozetic, I., "Compression of the ECG Knowledge-base Using the AQ Inductive Learning Algorithm," Reports of the Intelligent Systems Group, ISG 85-13, UIUCDCS-F-85-943, Department of Computer Science, University of Illinois, Urbana, March 1985.

P 85-15
Michalski, R. S. and Reinke, R., "Incremental Learning of Decision Rules: A Method and Experimental Results," , presented at the Machine Intelligence Workshop II, March 1985.

P 85-16
Michalski, R. S., "Knowledge Repair Mechanisms: Evolution vs Revolution," Reports of the Intelligent Systems Group, ISG 85-14, UIUCDCS-F-85-946, Department of Computer Science, University of Illinois, Urbana, July 1985.

P 85-17
Rendell, L., "Utility Patterns as Criteria for Efficient Generalization Learning," UIUCDCS-R-85-1206, Department of Computer Science, University of Illinois, April 1985.

P 85-18
Rendell, L., "Induction, of and by Probability," UIUCDCS-R-85-1209, Department of Computer Science, University of Illinois, Urbana, April 1985.

P 85-19
Rendell, L., "A Scientific Approach to Practical Induction," UIUCDCS-R-85-1211, Department of Computer Science, University of Illinois, Urbana, May 1985.

P 85-20
Rendell, L., "Genetic Plans and the Probabilistic Learning System: Synthesis and Results," UIUCDCS-R-85-1217, Department of Computer Science, University of Illinois, Urbana, July, 1985.

P 85-21
Fermanian, T., Michalski, R. S. and Katz, B., "An Expert System to Assist Turfgrass Managers in Weed Identification," Proceedings of the 1985 Summer Computer Simulation Conference, Chicago, IL, July, 1985.

P 85-22
Becker, J., "Inductive Learning of Decision Rules with Exceptions: Methodology and Experimentation," Reports of the Intelligent Systems Group, ISG 85-14, UIUCDCS-F-85-945, Master of Science Thesis, Department of Computer Science, University of Illinois, Urbana, August, 1985.

P 85-23
Falkenhainer, B., "Quantitative Empirical Learning: An Analysis and Methodology," Reports of the Intelligent Systems Group, ISG 85-16, UIUCDCS-F-85-947, Master of Science Thesis, Department of Computer Science, University of Illinois, Urbana, August, 1985.

P 85-24
Michalski, R. S. and Winston, P. H., "Variable Precision Logic," Artificial Intelligence Memo (An updated version appeared in AI Journal), No. 857, MIT, Cambridge, MA, September 1985.

P 85-25
Michalski, R. S. and Durham, T., "Trying to Mimic the Mind," (An article about research done by R.S.M. and his collaborators), in Computing Magazine, April 18, 1985.

P 85-26
Michalski, R. S., "Equipment of Artificial Intelligence Laboratory," , Department of Computer Science, University of Illinois, Urbana, 1985.

P 85-27
De Jong, K., "Genetic Algorithms: A 10 Year Perspective," Proceedings of the First International Conference on Genetic Algorithms and Their Applications, Pittsburgh, PA, July, 1985.

P 85-28
Michalski, R. S., "Knowledge Repair Mechanisms: Evolution vs Revolution," Proceedings of the Third International Machine Learning Workshop, Skytop, Rutgers University, June, 1985.

P 85-29
Rendell, L., "Substantial Constructive Induction Using Layered Information Compression: Tractable Feature Formation in Search," Revised paper, Proceedings of the Ninth International Joint Conference on Artificial Intelligence, University of California at Los Angeles, 1985.

P 85-30
Rendell, L., "Utility Patterns as Criteria for Efficient Generalization Learning," Proceedings of the 1985 Conference on Intelligent Systems and Machines, Rochester, MI, April 1985.

P 85-31
Michalski, R. S., "Knowledge Repair Mechanisms: Evolution vs Revolution," Proceedings of the Third International Machine Learning Workshop, Skytop, Rutgers University, pp. 116-119, June 24-26, 1985.

P 85-32
Rendell, L., "Induction, of and by Probability," Proceedings of the Workshop on Uncertainty and Probability in Artificial Intelligence,Sponsored by AAAI and IEEE, University of California at Los Angeles, August 1985.

P 85-33
Rendell, L., "Genetic Plans and the Probabilistic Learning System: Synthesis and Results," Proceedings of the International Conference on Genetic Algorithms and Their Applications, Carnegie-Mellon University, July, 1985.

P 85-34
Rendell, L., "Genetic Plans and the Probabilistic Learning System: Synthesis and Results(revised version)," Machine Learning: A Guide to Current Research, Kluwer Publishing Company, 1985.

P 85-35
Rendell, L., "A Scientific Approach to Practical Induction," Proceedings of the Third International Machine Learning Workshop, Skytop Lodge, Rutgers University, June 1985.

P 85-36
Rendell, L., "A Scientific Approach to Practical Induction(revised version)," Machine Learning: A Guide to Current Research, Kluwer Publishing Company, 1985.

1984

P 84-1
Pua, K. E., "Translating Annotated Predicate Calculus to PROLOG," Reports of the Intelligent Systems Group, ISG 84-1, UIUCDCS-F-918, Department of Computer Science, University of Illinois, Urbana, June, 1984.

P 84-2
Channic, T. D., "ADVISECORE: A Screen Package for Expert Systems," Reports of the Intelligent Systems Group, ISG 84-2, UIUCDCS-F-84-919, Department of Computer Science, University of Illinois, Urbana, July, 1984.

P 84-3
Rodewald, L. E., "BABY: An Expert System for Patient Monitoring in a Newborn Intensive Care Unit," M.S. Thesis, Reports of the Intelligent Systems Group, ISG 84-3, UIUCDCS-F-84-920, Department of Computer Science, University of Illinois, Urbana, July, 1984.

P 84-4
Reinke, R., "Knowledge Acquisition and Refinement Tools for the ADVISE META-EXPERT System," M.S. Thesis, Reports of the Intelligent Systems Group, ISG 84-4, UIUCDCS-F-84-921, Department of Computer Science, University of Illinois, Urbana, July, 1984.

P 84-5
Baim, P., "Automated Acquisition of Decision Rules: The Problems of Attribute Construction and Selection," MS Thesis,Reports of the Intelligent Systems Group, ISG 84-5, UIUCDCS-F-84-922, Department of Computer Science, University of Illinois, Urbana, July, 1984.

P 84-6
Michalski, R. S., "Inductive Learning as Rule-Guided Generalization of Symbolic Descriptions: A Theory and Implementation," Automatic Program Construction Techniques, pp. 517-552, Macmillan Publishing Company, New York, 1984.

P 84-7
Stepp, R., "Conjunctive Conceptual Clustering: A Methodology and Experimentation," Ph.D Thesis, UIUCDCS-R-84-1189, Department of Computer Science, University of Illinois, Urbana, September, 1984.

P 84-8
Michalski, R. S., "Learning Strategies and Automated Knowledge Acquisition: An Overview," Reports of the Intelligent Systems Group, ISG 84-6, UIUCDCS-F-84-926, Department of Computer Science, University of Illinois, Urbana, November, 1984.

P 84-9
Falkenhainer, B., "ABACUS: Adding Domain Constraints to Quantitative Scientific Discovery," Reports of the Intelligent Systems Group, ISG 84-7, UIUCDCS-F-84-927, Department of Computer Science, University of Illinois, Urbana, November , 1984.

P 84-10
Pua, K. E., "An Annotated Predicate Calculus Inference System (APCIS)," Reports of the Intelligent Systems Group, ISG 84-8, UIUCDCS-F-84-928, Department of Computer Science, University of Illinois, Urbana, November, 1984.

P 84-11
Nowicki, A. R., "A Comparison of Performances of a SUN-2 Workstation, VAX 11/780, and the Xerox Dolphin on a Learning Algorithm," Reports of the Intelligent Systems Group, ISG 84-9, UIUCDCS-F-84-929, Department of Computer Science, University of Illinois, Urbana, December, 1984.

P 84-12
De Jong, K., "Applying AI to the Diagnosis of Complex Systems," Proceedings of the Conference on Intelligent Systems and Machines, Rochester, MI, April 1984.

1983

P 83-1
Michalski, R. S. and Stepp, R., "Learning from Observation: Conceptual Clustering," Chapter in the book, Machine Learning: An Artificial Intelligence Approach, R. S. Michalski, T. J. Carbonell and T. M. Mitchell (Eds.), pp. 331-363, TIOGA Publishing Co., Palo Alto, 1983.

P 83-2
Carbonell, T. J., Michalski, R. S. and Mitchell, T. M., "An Overview of Machine Learning," Chapter in the book, Machine Learning: An Artificial Intelligence Approach, R. S. Michalski, T. J. Carbonell and T. M. Mitchell (Eds.), pp. 3-23, TIOGA Publishing Co., Palo Alto, 1983.

P 83-3
Michalski, R. S., "A Theory and Methodology of Inductive Learning," Chapter in the book, Machine Learning: An Artificial Intelligence Approach, R. S. Michalski, T. J. Carbonell and T. M. Mitchell (Eds.), pp. 83-134, TIOGA Publishing Co., Palo Alto, 1983.

P 83-4
Dietterich, T. G. and Michalski, R. S., "A Comparative Review of Selected Methods for Learning from Examples," Chapter in the book, Machine Learning: An Artificial Intelligence Approach, R. S. Michalski, T. J. Carbonell and T. M. Mitchell (Eds.), pp. 41-81, TIOGA Publishing Co., Palo Alto, 1983.

P 83-5
Machine Learning: An Artificial Intelligence Approach, Palo Alto, TIOGA Publishing Co., Palo Alto, 1983.

P 83-6
Bisht, V. S., Davis, J. H., Michalski, R. S. and Sinclair, J. B., "A Computer-Based Advisory System for Diagnosing Soybean Diseases in Illinois Plant Disease ," , pp. 459-463, April 1983.

P 83-7
Cramm, S., "ESEL/2: A Program for Selecting the Most Representative Training Events for Inductive Learning," Reports of the Intelligent Systems Group, ISG 83-1, UIUCDCS-F-83-901, Department of Computer Science, University of Illinois, Urbana, January 1983.

P 83-8
Pollack, J., "Relevant Variable Selection for Inductive Learning Programs," Reports of the Intelligent Systems Group, ISG 83-2, UIUCDCS-F-83-902, Department of Computer Science, University of Illinois, Urbana, January 1983.

P 83-9
Seyler, M., "A Knowledge Guided Image Interpretation Program," Reports of the Intelligent Systems Group, ISG 83-3, UIUCDCS-F-83-903, Department of Computer Science, University of Illinois, Urbana, January 1983.

P 83-10
Hoff, W., Michalski, R. S. and Stepp, R., "INDUCE 2: A Program for Learning Structural Descriptions from Examples," Reports of the Intelligent Systems Group, ISG 83-4, UIUCDCS-F-83-904, Department of Computer Science, University of Illinois, Urbana, January 1983.

P 83-11
Michalski, R. S. and Larson, J., "Incremental Generation of VL1 Hypotheses: The Underlying Methodology and the Description of Program AQ11," Reports of the Intelligent Systems Group, ISG 83-5, UIUCDCS-F-83-905, Department of Computer Science, University of Illinois, Urbana, January 1983.

P 83-12
Michalski, R. S., "A Theory and Methodology of Inductive Learning, (Modified version of 1983-3)," Artificial Intelligence, pp. 111-161, 1983.

P 83-13
Stauffer, M. and Michalski, R. S., "Determining Computer Architectures and Compiler Structures Through Inductive Inference: A Preliminary Investigation," Reports of the Intelligent Systems Group, ISG 83-6, UIUCDCS-F-83-906, Department of Computer Science, University of Illinois, Urbana, January 1983.

P 83-14
Vaidya, P., "A Representation Scheme for Constructive Induction," Reports of the Intelligent Systems Group, ISG 83-7, UIUCDCS-F-83-907, Department of Computer Science, University of Illinois, Urbana, January 1983.

P 83-15
Orejel-Opisso, J. L., "On the Representation of Rules," Reports of the Intelligent Systems Group, ISG 83-8, UIUCDCS-F-83-908, Department of Computer Science, University of Illinois, Urbana, January 1983.

P 83-16
Michalski, R. S. and Stepp, R., "Conjunctive Conceptual Clustering: Classification Using Background Knowledge," Submitted to the North American Branch of the Classification Society, Philadelphia, May 29-31, 1983.

P 83-17
Vaidya, P., "On Induction Experiments," Reports of the Intelligent Systems Group, ISG 83-9, UIUCDCS-F-83-909, Department of Computer Science, University of Illinois, Urbana, January 1983.

P 83-18
Michalski, R. S., "Inductive Learning: A Review of Some Recent Work," Invited paper,Third Yale Workshop on Applications of Adaptive Systems Theory, June 15-17,1983.

P 83-19
Proceedings of the International Machine Learning Workshop, University of Illinois Allerton House, Urbana, June 22-24, 1983.

P 83-20
Michalski, R. S. and Stepp, R., "How to Structure Structured Objects," Proceedings of the International Machine Learning Workshop, University of Illinois Allerton House,Urbana, pp. 156-160, June 22-24,1983.

P 83-21
Dietterich, T. G. and Michalski, R. S., "Discovering Patterns in Sequences of Events," Proceedings of the International Machine Learning Workshop, University of Illinois Allerton House,Urbana, pp. 41-57, June 22-24,1983.

P 83-22
Michalski, R. S. and Stepp, R., "Automated Construction of Classifications: Conceptual Clustering versus Numerical Taxonomy," IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. PAMI-5, No. 4, pp. 396-410, July, 1983.

P 83-23
Biswas, B., "A Programmer's Guide for CLUSTER, A Program for Conjunctive Clustering," Reports of the Intelligent Systems Group, ISG 83-10,UIUCDCS-F-83-910, Department of Computer Science, University of Illinois,Urbana, July 1983.

P 83-24
Boulanger, A., "The Expert System Plant/CD: A Case Study in Applying the General Purpose Inference System Advise to Predicting Black Cutworm Damage in Corn," M.S. Thesis, UIUCDCS-R-83-1134, Department of Computer Science, University of Illinois, Urbana, July 1983..

P 83-25
Michalski, R. S. and Baskin, A. B., "Integrating Multiple Knowledge Representations and Learning Capabilities in an Expert System: The ADVISE System," Proceedings of the 8th IJCAI Meeting, Karlsruhe, West Germany, pp. 256-258, 1983.

P 83-26
Carbonell, T. J., Michalski, R. S. and Mitchell, T. M., "Machine Learning: A Historical and Methodological Analysis," AI Magazine, pp. 69-79, 1983.

P 83-27
Baskin, A. B., Michalski, R. S. and Spackman, K. A., "A Logic-Based Approach to Conceptual Data Base Analysis,," Med. Inform, Vol. 8, No. 3, pp. 187-195, 1983.

P 83-28
Becker, J., "AQINTERLISP: An INTERLISP Program for Inductive Generalization of VL1Event Sets, User's and Programmer's Guide," Reports of the Intelligent Systems Group, ISG 83-11, UIUCDCS-F-83-911, Department of Computer Science, University of Illinois, Urbana, September 1983.

P 83-29
Reinke, R., "PLANT/DS: An Expert System for the Diagnosis of Soybean Diseases Common in Illinois, User's Guide and Program Description," Reports of the Intelligent Systems Group, ISG 83-12, UIUCDCS-F-83-912, Department of Computer Science, University of Illinois, Urbana, October 1983.

P 83-30
Stepp, R., "A Description and User's Guide for CLUSTER/2, A Program for Conjunctive Conceptual Clustering," Report No. UIUCDCS-R-83-1084, Department of Computer Science, University of Illinois, Urbana, November 1983.

P 83-31
Spackman, K. A., "QUIN: Integration of Inferential Operators within a Relational Database," Reports of the Intelligent Systems Group, ISG 83-13, UIUCDCS-F-83-917, M.S. Thesis, Department of Computer Science, University of Illinois, Urbana, 1983.

P 83-32
Michalski, R. S., "A Theory and Methodology of Inductive Learning (Modified version of 1983-3)," Report No. UIUCDCS-R-83-1122, Department of Computer Science, University of Illinois, Urbana, January 1983.

P 83-33
De Jong, K., "Intelligent Control: Integrating AI and Control Theory," Proceedings of the IEEE Trends and Applications Conference, Washington, DC, May 1983.

1982

P 82-1
Stepp, R., "INDUCE 1.2, A Program for Learning Structural Descriptions from Examples (Program Listing)," Internal Report, Department of Computer Science, University of Illinois, Urbana, March 1982.

P 82-2
Michalski, R. S. and Stepp, R., "Conjunctive Conceptual Clustering: Further Results," Abstracts of the Classification Society and the Psychometric Society Meeting, Montreal, May 30 to June 2, 1982.

P 82-3
Badger, D. G., Campbell, R., Dershowitz, N., Harandi, M. T., Laursen, A., Michalski, R. S., Michie, D., Penka, R. and Simmonds, M., "Knowledge based programming assistant, KBPA-1," UIUCDCS-F-82-894, Department of Computer Science, University of Illinois, Urbana, April 1982.

P 82-4
Michalski, R. S., Davis, J. H., Bisht, V. S. and Sinclair, J. B., "PLANT/DS: An Expert Consulting System for the Diagnosis of Soybean Diseases," Plant Diseases and Proceedings of the First European Conference on Artificial Intelligence, Orsay, France, pp. 133-138, July 12-14,1982.

P 82-5
Baim, P., "The PROMISE Method For Selecting Most Relevant Attributes For Inductive Learning Systems," Reports of the Intelligent Systems Group, ISG 82-1, UIUCDCS-F-82-898, Department of Computer Science, University of Illinois, Urbana, September 1982.

P 82-6
O'Rorke, P., "A Comparative Study of Inductive Learning Systems AQ11P and ID-3 Using a Chess Endgame Test Problem," Reports of the Intelligent Systems Group, ISG 82-2, UIUCDCS-F-82-899, Department of Computer Science, University of Illinois, Urbana, September 1982.

P 82-7
Uhrik, C. T., "PLANT/DS Revisited: Non-Homogeneous Evaluation Schema in Expert Systems," Proceedings of the National Conference on Artificial Intelligence, AAAI-82, Pittsburgh, August 18-20, 1982.

P 82-8
Michalski, R. S., Baskin, A. B. and Spackman, K. A., "A Logic-based Approach to Conceptual Database Analysis," 6th Annual Symposium on Computer Applications in Medical Care (SCAMC-6), George Washington University Medical Center, Washington, DC, pp. 792-796, November 1-2, 1982.

P 82-9
Michalski, R. S. and Stepp, R., "Revealing Conceptual Structure in Data by Inductive Inference," Chapter in the book, Machine Intelligence 10, D. Michie, J. E. Hayes and H-H. Pao (Eds.), New York, pp. 173-196, Ellis Horwood Ltd., 1982.

P 82-10
Layman, T. C., "OPTREE: A Program for Transfering Decision Tables to Optimal or Suboptimal Decision Trees," a revised version of 1979 report, Department of Computer Science, University of Illinois, Urbana, 1982.

1981

P 81-1
Michalski, R. S., "An Application of Inductive Inference to Determining Computer Architecture and Compiler Structure," Internal Report, Department of Computer Science, University of Illinois, Urbana, February 1981.

P 81-2
Michalski, R. S., Stepp, R. and Diday, E., "A Recent Advance in Data Analysis: Clustering Objects into Classes Characterized by Conjunctive Concepts," Invited chapter in the book Progress in Pattern Recognition, L. Kanal and A. Rosenfeld (Eds.), Vol. 1, pp. 33-55, North-Holland, 1981.

P 81-3
SIGART Special Issue on Machine Learning, T. M. Mitchell, T. J. Carbonell and R. S. Michalski (Eds.), SIGART No. 76, April 1981.

P 81-4
Michalski, R. S. and Stepp, R., "A Method of Organizing Data into Conceptual Hierarchies," Proceedings of the Classification Society Meeting, Toronto, May 31 - June 2, 1981.

P 81-5
Dietterich, T. G. and Michalski, R. S., "Inductive Learning of Structural Descriptions: Evaluation Criteria and Comparative Review of Selected Methods," Artificial Intelligence Journal, Vol. 16, No. 3, pp. 257-294, July 1981.

P 81-6
Collins, A. and Michalski, R. S., "Toward a Formal Theory of Human Plausible Reasoning," Proceedings of the 3rd Annual Conference of the Cognitive Science Society, Berkeley, California, August 19-21, 1981.

P 81-7
Michalski, R. S. and Stepp, R., "An Application of AI Techniques to Structuring Objects into an Optimal Conceptual Hierarchy," Proceedings of the 7th IJCAI, Vancouver, Canada, August 24-28, 1981.

P 81-8
Davis, J., "Convart: A Program for Constructive Induction on Time Dependent Data," M.S. Thesis, Department of Computer Science, University of Illinois, Urbana, September 1981.

P 81-9
Michalski, R. S. and Stepp, R., "Concept-based Clustering versus Numerical Taxonomy," Report No. 1073, Department of Computer Science, University of Illinois, Urbana, October 1981.

P 81-10
Michalski, R. S. and Chilausky, R., "Knowledge Acquisition by Encoding Expert Rules versus Computer Induction From Examples: A Case Study Involving Soybean Pathology," Fuzzy Reasoning and its Applications, B. Gaines and E. H. Mamdani (Eds.), 1981.

1980

P 80-1
Dietterich, T. G. and Michalski, R. S., "Learning and Generalization of Structural Descriptions: Evaluation Criteria and Comparative Review of Selected Methods," Report No. 1007, Department of Computer Science, University of Illinois, Urbana, February 1980.

P 80-2
Michalski, R. S. and Chilausky, R., "Learning by Being Told and Learning from Examples: An Experimental Comparison of the Two Methods of Knowledge Acquisition in the Context of Developing an Expert System for Soybean Disease Diagnosis," International Journal of Policy Analysis and Information Systems, Vol. 4, No. 2, 1980.

P 80-3
Dietterich, T. G., "Programmer's Guide to the Eleusis Program," Internal Report, Department of Computer Science, University of Illinois, Urbana, May 1980.

P 80-4
Dietterich, T. G., "The Methodology of Knowledge Layers for Inducing Descriptions of Sequentially Ordered Events," M.S. Thesis and Report No. 1024, Department of Computer Science, University of Illinois, Urbana, May 1980.

P 80-5
Michalski, R. S., "Pattern Recognition as Rule-Guided Inductive Inference," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-2, No. 4, pp. 349-361, July 1980.

P 80-6
Michalski, R. S. and Chilausky, R., "Knowledge Acquisition by Encoding Expert Rules versus Computer Induction From Examples: A Case Study Involving Soybean Pathology," International Journal for Man-Machine Studies, No. 12, pp. 63-87, 1980.

P 80-7
Michalski, R. S., "Inductive Learning as Rule-Guided Generalization and Conceptual Simplification of Symbolic Descriptions: Unifying principles and a methodology," Workshop on Current Developments in Machine Learning, Carnegie-Mellon University, Pittsburgh, July 16-18, 1980.

P 80-8
Stepp, R., "Learning from Observations: Experiments in Conceptual Clustering," Workshop on Current Developments in Machine Learning, Carnegie-Mellon University, Pittsburgh, July 16-18, 1980.

P 80-9
Dietterich, T. G., "Multiple-Model Induction in Eleusis," Workshop on Current Developments in Machine Learning, Carnegie-Mellon University, Pittsburgh, July 16-18, 1980.

P 80-10
Michalski, R. S., "Adaptation through Generalization," Invited paper at the Fifth Annual Ann Arbor Adaptive Systems Workshop, University of Michigan, Ann Arbor, Michigan, July 21-23, 1980.

P 80-11
Michalski, R. S., "Inductive Inference as Rule-Guided Transformation of Symbolic Descriptions," Invited paper for the International Workshop on Program Construction, Chateau de Bonas (France), September 8-12.

P 80-12
Michalski, R. S., "Knowledge Acquisition Through Conceptual Clustering: A Theoretical Framework and an Algorithm for Partitioning Data into Conjunctive Concepts," Journal of Policy Analysis and Information Systems, Vol. 4, No. 3, pp. 219-244, September 1980.

P 80-13
Boulanger, A., "A Description of the Display Module for Interactive Presentation of Visual Information on a Plasma Terminal (ORION)," Internal Report, Department of Computer Science, University of Illinois, Urbana, 1980.

P 80-14
Michalski, R. S., "Inductive Inference as Rule-Guided Transformation of Symbolic Descriptions," Automatic Program Construction and Techniques, Y. Kodratoff, A. W. Biermann and G. Guiho (Eds.), pp. 517-552, MacMillian Publishing Company, 1980.

P 80-15
Michalski, R. S., "Knowledge Acquisition Through Conceptual Clustering: A Theoretical Framework and an Algorithm for Partitioning Data into Conjunctive Concepts," Report No. UIUCDCS-R-80-1026, Department of Computer Science, University of Illinois, Urbana, 1980.

1979

P 79-1
Chilausky, R., "A Prototype Computer Based Consulting System using Variable Valued Logic System VL1: Methodology and Implementation," M.S. Thesis, Department of Computer Science, University of Illinois, Urbana, January 1979.

P 79-2
Stepp, R., "The Uniclass Inductive Program AQ7UN1: Program Implementation and User's Guide," Report No. 949, Department of Computer Science, University of Illinois, Urbana, July 1979.

P 79-3
Stepp, R., "Learning Without Negative Examples via Variable-Valued Logic Characterizations: The Uniclass Inductive Program AQ7UN1," Report No. 982, Department of Computer Science, University of Illinois, Urbana, July, 1979.

P 79-4
Michalski, R. S., "Conceptual Clustering: A Theoretical Foundation and a Method for Partitioning Data into Conjunctive Concepts," Seminaries IRIA, Classification Automatique et Perception par Ordinateur, INRIA, France, pp. 253-295, 1979.

P 79-5
Michalski, R. S., "Detection of Conceptual Patterns Through Inductive Inference," Seminaries IRIA, Classification Automatique et Perception par Ordinateur, INRIA, France, pp. 297-339, 1979.

P 79-6
Dietterich, T. G. and Michalski, R. S., "Learning and Generalization of Characteristic Descriptions: Evaluation Criteria and Comparative Review of Selected Methods," Proceedings of the Sixth International Joint Conference on Artificial Intelligence, Tokyo, pp. 223-231, August 20-23,1979.

P 79-7
Layman, T. C., "A PASCAL Program to Convert Extended Entry Decision Tables Into Optimal Decision Trees," Internal Report, Department of Computer Science, University of Illinois, Urbana, October 1979.

P 79-8
Reiter, J., "A Program that Paraphrases Variable-Valued Logic Formulas," Internal Report, Department of Computer Science, University of Illinois, Urbana, IL, October, 1979.

P 79-9
Richards, P., "AQLISP: A LISP Program for Inductive Generalization of VL1 Event Sets," Internal Report, Department of Computer Science, University of Illinois, Urbana, December, 1979.

1978

P 78-1
Michalski, R. S., "A Planar Geometrical Model for Representing Multi-Dimensional Discrete Spaces and Multiple-Valued Logic Functions," Report No. 897, Department of Computer Science, University of Illinois, Urbana, January 1978.

P 78-2
Michalski, R. S., "Designing Extended Entry Decision Tables and Optimal Decision Trees Using Decision Diagrams," Report No. 898, Department of Computer Science, University of Illinois, Urbana, March 1978.

P 78-3
Michalski, R. S. and Larson, J., "Selection of Most Representative Training Examples and Incremental Generation of VL1 Hypotheses: The Underlying Methodology and the Description of Programs ESEL and AQ11," Report No. 867, Department of Computer Science, University of Illinois, Urbana, May 1978.

P 78-4
Michalski, R. S., "Pattern Recognition as Knowledge-Guided Computer Induction," Report No. 927, Department of Computer Science, University of Illinois, Urbana, June 1978.

P 78-5
Dietterich, T. G., "Description of Inductive Program INDUCE 1.1," Internal Report, Department of Computer Science, University of Illinois, Urbana, October 1978.

P 78-6
Lubars, M., "A Discussion of Plausible Inferences and a Formalization of Some Inference Rules," Internal Report, Department of Computer Science, University of Illinois, Urbana, December 1978.

1977

P 77-1
Michalski, R. S. and Negri, P., "An Experiment on Inductive Learning in Chess End Games," Machine Representation of Knowledge, MACHINE INTELLIGENCE 8, pp. 175-192, Ellis Horwood, 1977.

P 77-2
Negri, P., "Inductive Learning in a Hierarchical Model for Representing Knowledge," Machine Representation of Knowledge, MACHINE INTELLIGENCE 8, pp. 193-206, Ellis Horwood, 1977.

P 77-3
Michalski, R. S., "Toward Computer-Aided Induction: A Brief Review of Currently Implemented AQVAL Programs," Report No. 874, Department of Computer Science, University of Illinois, Urbana, 1977.

P 77-4
Yalow, E., "YAQ: A 360 Assembler Version of the Algorithm Aq and Comparison with Other PL/1 Programs," Report No. 840, Department of Computer Science, University of Illinois, Urbana, May 1977.

P 77-5
Larson, J., "Inductive Inference in the Variable-Valued Predicate Logic SystemsVL21: Methodology and Computer Implementation," Ph.D. Thesis, Report No.869, Department of Computer Science, University of Illinois, Urbana, May 1977.

P 77-6
Larson, J., "INDUCE-1: An Interactive Inductive Inference Program in VL21 Logic System," Report No. 876, Department of Computer Science, University of Illinois, Urbana, May 1977.

P 77-7
Larson, J. and Michalski, R. S., "Inductive Inference of VL Decision Rules," Invited paper for the Workshop in Pattern-Directed Inference Systems, Hawaii, and published in SIGART Newsletter, ACM, No. 63, pp. 38-44, June 1977, May 23-27, 1977.

P 77-8
Michalski, R. S., "A System of Programs for Computer-Aided Induction: A Summary," Proceedings of the Fifth International Joint Conference on Artificial Intelligence, MIT, Cambridge, Massachusetts, pp. 319-320, August 22-25,1977.

P 77-9
Schubert, R., "The VL Relational Data Sublanguage for an Inferential Computer Consultant," Master's Thesis, Report No. 846, Department of Computer Science, University of Illinois, Urbana, October 1977.

P 77-10
Bitner, J. R., "Capacity and Efficiency of Decision Functions," IEEE Transactions on Computers, Vol. C-26, No. 11, pp. 1147-1151, November 1977.

1976

P 76-1
Michalski, R. S., "Learning by Inductive Inference," Computer Oriented Learning Processes, NATO Advanced Study Institutes Series, Series E, No. 14, pp. 321-337, 1976.

P 76-2
Chilausky, R., Jacobsen, B. and Michalski, R. S., "An Application of Variable-Valued Logic to Inductive Learning of Plant Disease Diagnostic Rules," Proceedings of the 1976 International Symposium on Multiple-Valued Logic, Utah State University, Logan, Utah, May 25-28, 1976.

P 76-3
Larson, J., "A Multi-Step Formation of Variable-Valued Logic Hypotheses," Proceedings of the 1976 International Symposium on Multiple-Valued Logic, Utah State University, Logan, Utah, May 25-28, 1976.

P 76-4
Forsburg, S., "AQPLUS: An Adaptive Random Search Method for Selecting a Best Set of Attributes from a Large Collection of Candidates," Internal Report, Department of Computer Science, University of Illinois, Urbana, 1976.

1975

P 75-1
Michalski, R. S., "Synthesis of Optimal and Quasi-Optimal Variable-Valued Logic Formulas," Proceedings of the 1975 International Symposium on Multiple-Valued Logic, Bloomington, Indiana, pp. 76-87, May 13-16, 1975.

P 75-2
Cuneo, R. P., "Selected Problems of Minimization of Variable-Valued Logic Formulas," Masters Thesis, Report No. 726, Department of Computer Science, University of Illinois, Urbana, May 1975.

P 75-3
Jensen, G. M., "SYM-1: A Program that Detects Symmetry of Variable-Valued Logic Functions," Report No. 729, Department of Computer Science, University of Illinois, Urbana, May 1975.

P 75-4
Michalski, R. S., "Variable-Valued Logic and Its Applications to Pattern Recognition and Machine Learning," Computer Science and Multiple-Valued Logic Theory and Applications, pp. 506-534, North-Holland Publishing Co., 1975.

P 75-5
Michalski, R. S. and Larson, J., "AQVAL/1 (AQ7) User's Guide and Program Description," Report No. 731, Department of Computer Science, University of Illinois, Urbana, June 1975.

P 75-6
Michalski, R. S., "On the Selection of Representative Samples from Large Relational Tables for Inductive Inference," Report No. M.D.C. 1.1.9, Department of Information Engineering, University of Illinois at Chicago Circle, Chicago, July 1975.

P 75-7
Jensen, G. M., "Determination of Symmetric VL1 Formulas: Algorithm and Program SYM4," M.S. Thesis, Report No. 774, Department of Computer Science, University of Illinois, Urbana, December 1975.

1974

P 74-1
Michalski, R. S., "Variable-Valued Logic: System VL1," Proceedings of the 1974 International Symposium on Multiple-Valued Logic, West Virginia University, Morgantown, West Virginia, pp.323-346, May 29-31, 1974.

P 74-2
Michalski, R. S., "A Variable Decision Space Approach for Implementing a Classification System," Proceedings of the Second International Joint Conference on Pattern Recognition, Copenhagen, Denmark, pp. 71-75, August 13-15, 1974.

P 74-3
Michalski, R. S., "Problems of Designing an Inferential Medical Consulting System," Proceedings of the First Illinois Conference on Medical Information Systems, Urbana, pp. 151-157 , October 17-18, 1974.

P 74-4
Baskin, A. B., "A Comparative Discussion of Variable-Valued Logic and Grammatical Inference," Report No. 663, Department of Computer Science, University of Illinois, Urbana, 1974.

P 74-5
Michalski, R. S., "A Logic-Based Approach to Optimal Classification into a Large Number of Classes," Internal Report, 1974.

P 74-6
"OMNIBUS: A Program for Quantization of Variables and Evaluation of Inductively Derived Logic Formulas," Internal Report, Department of Computer Science, University of Illinois, Urbana, August 1974.

1973

P 73-1
Michalski, R. S., "Discovering Classification Rules Using Variable-Valued Logic SystemVL1," Proceedings of the Third International Joint Conference on Artificial Intelligence, Stanford, CA, pp. 162-172, August 20-23, 1973.

P 73-2
Michalski, R. S., "AQVAL/1--Computer Implementation of a Variable-Valued Logic System VL1 and Examples of its Application to Pattern Recognition," Proceedings of the First International Joint Conference on Pattern Recognition, Washington, DC, pp. 3-17, October 30 - November 1, 1973.

1972

P 72-1
Michalski, R. S., "A Variable-Valued Logic System as Applied to Picture Description and Recognition," Graphic Languages, F. Nake and A. Rosenfeld (Eds.), North-Holland Publishing Co., 1972.

1971

P 71-1
Michalski, R. S. and McCormick, B. H, "Interval Generalization of Switching Theory," Proceedings of the Third Annual Houston Conference on Computer and System Science, Houston, Texas, April 26-27, 1971.

P 71-2
Michalski, R. S. and McCormick, B. H, "Interval Generalization of Switching Theory," (An extended version of above paper), Report No. 442, Department of Computer Science, University of Illinois, Urbana, May 3, 1971.

P 71-3
Michalski, R. S., "A Geometrical Model for the Synthesis of Interval Covers," Report No. 461, Department of Computer Science, University of Illinois, Urbana, June 24, 1971.

P 71-4
Michalski, R. S. and Kulpa, Z., "A System of Programs for the Synthesis of Switching Circuits Using the Method of Disjoint Stars," Information Processing 71, pp. 61-65, North-Holland Publishing Co, 1971.

P 71-5
Michalski, R. S., "Minimization and Recognition of Symmetry of Logic Functions", published in Polish under the title: "Synteza wyrazen minimalnych i rozpoznawanie symetrii funkcji logicznych," Prace Instytutu Automatyki PAN, Zeszyt 92, Warszawa, Instytut Automatyki Polskiej Akademii Nauk, 1971.

1970

P 70-1
Michalski, R. S., "Automatic Synthesis of the Quasi-Minimal Multiple-Output Switching Circuits," Proceedings of the VI International Symposium on Information Processing (FCIP), Yugoslavia,Bled, pp. 1-7, September 23-26, 1970.

1969

P 69-1
Michalski, R. S., "Recognition of Total or Partial Symmetry in a Completely or Incompletely Specified Switching Function," Proceedings of the IV Congress of the International Federation on Automatic Control (IFAC) (Finite Automata and Switching Systems), Vol. 27 , Warsaw, pp. 109-129, June 16-21, 1969.

P 69-2
Michalski, R. S., "On the Quasi-Minimal Solution of the General Covering Problem," Proceedings of the V International Symposium on Information Processing (FCIP 69)(Switching Circuits) , Vol. A3 , Yugoslavia, Bled, pp. 125-128, October 8-11, 1969.

1968

P 68-1
Michalski, R. S., "On the Problems of Buidling Reading Machines," published in Polish under the title: "O problemach budowy automatow czytajacych," Maszyny Matematyczne. Zastosowania w Gospodarce, Technice i Nauce, 4, 1968.

1967

P 67-1
Michalski, R. S., "Graphical Minimization of Normal Expressions of Logic Functions Using Tables of the Veitch-Karnaugh Type," published in Polish under the title: "Graficzna minimalizacja w klasie alternatywnych normalnych wyrazen funkcji logicznych na podstawie tablic typu Veitcha-Karnaugha," Prace Instytutu Automatyki PAN, Zeszyt 52, Instytut Automatyki, Polska Akademia Nauk, 1967.

P 67-2
Michalski, R. S., "Some Problems in Design and Application of Reading Machines," Proceedings of the II National (Bulgarian) Conference on Automatic Control, vol. III, Bulgaria, Varna, Sept. 21-25, 1967.

1966

P 66-1
Karpinski, J. and Michalski, R. S., "A System for Learning and Recognition of Alpha-Numeric Characters: A Method and Computer Implementation," published in Polish under the title: "Perceprton dla znakow alfanumerycznych. Opis koncepcji projektu oraz modelu na maszynie cyfowej," Prace Instytutu Automatyki PAN, Zeszyt 35, Instytut Automatyki, Warszawa, Polska Akademia Nauk, 1966.