Publications by Ryszard S. Michalski


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Individual entities below are denoted by P numbers. For example, P 04-3 denotes Maloof, M. and Michalski R.S., "Incremental Learning with Partial Instance Memory," Artificial Intelligence, 154, 95-126, 2004. The MLI Technical Reports are denoted by MLI-#, where # is the number of the MLI Technical Report. For example MLI-02-1 with P number 02-5 denotes 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.

Books and Proceedings

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

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.

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

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

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.

Michalski, R. S. (Ed.), Multistrategy Learning, Kluwer Academic Publishers, 1993.

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

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.

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

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.

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

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

Book Chapters

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

Van Mechelen, I. and Michalski, R. S., "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.

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.

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.

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.

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

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.

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.

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

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.

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.

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.

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.

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.

Kaufman, K. and Michalski, R. S., "From Data Mining to Knowledge Mining," Handbook in Statistics, Vol. 24: Data Mining and Data Visualization, Rao, C.R., Solka, J.L. and Wegman, E.J. (Eds.), 47-75, Elsevier/North Holland, 2005.

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.

Referred Papers in Journals and Conference Proceedings

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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

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

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.

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.

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.

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

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.

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.

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

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

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

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

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.

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.

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

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.

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.

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.

Michalski, R. S., "Concept Learning," AI Encyclopedia, January 1986.

Michalski, R. S. and Stepp, R., "Clustering," AI Encyclopedia, January 1986.

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

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.

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.

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.

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.

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.

Haddawy, P., Ko, H., Chen, K., Iwanska, L. and Michalski, R. S., "Machine Learning and Inference: An Overview of Programs and Examples of their Performance," , Artificial Intelligence Laboratory, Department of Computer Science, University of Illinois at Urbana-Champaign, September, 1986.

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

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.

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

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.

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.

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

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.

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.

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.

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.

Bergadano, F., Matwin, S., Zhang, J. and Michalski, R. S., "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.

Dontas, K., Boehm-Davis, D. 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.

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

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

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

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.

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.

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.

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.

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.

Dontas, K., Boehm-Davis, D. 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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

Wnek, J. and Michalski, R. S., "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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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

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.

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.

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.

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.

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.

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.

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

Michalski, R. S. and Kaufman, K., "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.

Coletti, M., Lash, T., Mandsager, C., Michalski, R. S. and Moustafa, R., "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.

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

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.

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

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), Guimaraes, Portugal, pp 41-58, June 2000.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

Michalski, R. S., "Knowledge Mining: A Proposed New Direction," Invited talk at the Sanken Symposium on Data Mining and Semantic Web, Osaka University, Japan, March 10-11, 2003.

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

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).

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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 (mpg video file 380 MB).

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.

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.

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.

Technical Reports

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.

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.

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

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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

Ko, H., Chen, K. 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.

Baskin, A. B., Boulanger, A., Uhrik, C. T., Reinke, R., Channic, T. D., Rodewald, L. E., Borodkin, S. and Michalski, R. S., "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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Dontas, K., Boehm-Davis, D. 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.

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.

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.

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.

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.

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 .

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.

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.

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.

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.

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.

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.

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.

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

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 92-2, George Mason University, Fairfax, VA, January, 1992.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

Wnek, J. and Michalski, R. S., "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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

Li, Z., Kafatos, M. 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.

Zhang, Q. and Michalski, R. S., "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.

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.

Zhang, Q. and Michalski, R. S., "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.

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.

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.

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.

Coletti, M., Lash, T., Mandsager, C., Moustafa, R. and Michalski, R. S., "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.

Kaufman, K. and Michalski, R. S., "Discovering Multidimensional Patterns in Large Datasets Using Knowledge Scouts," Reports of the Machine Learning and Inference Laboratory, MLI 99-6, George Mason University, Fairfax, VA, June 1999.

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.

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.

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.

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.

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.

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.)

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)..

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.

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.

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.

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.

Kaufman, K. and Michalski, R. S., "Initial Considerations toward Knowledge Mining," Reports of the Machine Learning and Inference Laboratory, MLI 04-4, George Mason University, Fairfax, VA, October, 2004.

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.

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, Fairfax, VA, June, 2005.

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.

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, Fairfax, VA, November, 2005.

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.

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, Fairfax, VA, 2006.

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.

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, Fairfax, VA, June, 2006 (Updated: August 23, 2006).

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.

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.

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, George Mason University, Fairfax, VA, 2008.


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