Center for Discovery Science and Health Informatics College of Health and Human Services and Provost Office
Mission Faculty and Associates Machine Learning and Inference Laboratory Health Services Research Unit College of Health and Human Services Publications Software	Publications To view the publications from a specific year, click on the year from the list below: 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 1987 1986 1985 1984 1983 1982 1981 1980 1979 1978 1977 1976 1975 1974 1973 1972 1971 1970 1969 1968 1967 1966 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. Papers published before the creation of the Center for Discovery Science and Health Informatics on May 1, 2007, are publications of the Machine Learning and Inference Laboratory. 2007 P 07-1 Michalski, R. S. and Wojtusiak, J., "Semantic and Syntactic Attribute Types in AQ Learning," Reports of the Machine Learning and Inference Laboratory, MLI 07-1, George Mason University, Fairfax, VA, 2007. P 07-2 Michalski, R. S., Wojtusiak, J. and Kaufman, K., "Progress Report on the Learnable Evolution Model," Reports of the Machine Learning and Inference Laboratory, MLI 07-2, George Mason University, Fairfax, VA, 2007. P 07-3 Michalski, R. S. and Wojtusiak, J., "Generalizing Data in Natural Language," Proceedings of the International Conference Rough Sets and Emerging Intelligent Systems Paradigms, RSEISP'07, Lecture Notes in Computer Science, Springer, 2007. P 07-4 Michalski, R. S. and Pietrzykowski, J., "iAQ: A program that discovers rules," AAAI-07 AI Video Competition, Twenty-Second Conference on Artificial Intelligence (AAAI-07), Vancouver, British Columbia, July 22–26, 2007 (mpg video file 380 MB). P 07-5 Kaufman, K., Michalski, R. S., Pietrzykowski, J. and Wojtusiak, J., "An Integrated Multi-task Inductive Database and Decision Support System VINLEN: Initial Implementation and Early Results," Updated version of paper 06-9 accepted to be published in Lecture Notes in Computer Science, Springer P 07-6 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, 2007 (accepted). P 07-7 Wojtusiak, J. and Michalski, R. S., "Analyzing Diaries for Analytical Relapse Prevention Using Natural Induction: A Method and Preliminary Results," Quality Management in Health Care, 16, 4, 2007 (in press). P 07-8 Kaufman, K., Michalski, R. S., Pietrzykowski, J. and Wojtusiak, J., "The VINLEN Multi-task Inductive Database and Decision Support System: Current Status," Reports of the Machine Learning and Inference Laboratory, George Mason University, Fairfax, VA, 2007 (to appear). 2006 P 06-1 Michalski, R. S., "Machine Learning: A Historical Journey and Grand Challenges," Reports of the Machine Learning and Inference Laboratory, MLI 06-1, George Mason University, Fairfax, VA, 2006. P 06-2 Wojtusiak, J., Michalski, R. S., Kaufman, K. and Pietrzykowski, J., "Multitype Pattern Discovery Via AQ21: A Brief Description of the Method and Its Novel Features," Reports of the Machine Learning and Inference Laboratory, MLI 06-2, George Mason University, Fairfax, VA, June, 2006. P 06-3 Michalski, R. S., Kaufman, K., Pietrzykowski, J., Wojtusiak, J., Mitchell, S. and Seeman, W.D., "Natural Induction and Conceptual Clustering: A Review of Applications," Reports of the Machine Learning and Inference Laboratory, MLI 06-3, George Mason University, Fairfax, VA, June, 2006 (Updated: August 23, 2006). P 06-4 Wojtusiak, J. and Michalski, R. S., "The Use of Compound Attributes in AQ Learning," Proceedings of the Intelligent Information Processing and Web Mining Conference, IIPWM 06, Lecture Notes in Computer Science, Ustron, Poland, June 19-22, 2006. P 06-5 Kaufman, K., Wojtusiak, J., Pietrzykowski, J., Michalski, R. S. and Sniezynski, B., "Learning Symbolic User Models for Intrusion Detection: A Method and Initial Results," Proceedings of the Intelligent Information Processing and Web Mining Conference, IIPWM 06, Lecture Notes in Computer Science, Ustron, Poland, June 19-22, 2006. P 06-6 Wojtusiak, J., "Initial Study on Handling Constrained Optimization Problems in Learnable Evolution Model," Proceedings of The Graduate Student Workshop at Genetic and Evolutionary Computation Conference, GECCO 2006, Seattle, WA, July 8-12, 2006. P 06-7 Wojtusiak, J. and Michalski, R. S., "The LEM3 Implementation of Learnable Evolution Model and Its Testing on Complex Function Optimization Problems," Proceedings of Genetic and Evolutionary Computation Conference, GECCO 2006, Seattle, WA, July 8-12, 2006. P 06-8 Seeman, W.D. and Michalski, R. S., "The CLUSTER3 System for Goal-oriented Conceptual Clustering: Method and Preliminary Results," Proceedings of The Data Mining and Information Engineering 2006 Conference, Prague, Czech Republic, July 11-13, 2006. P 06-9 Kaufman, K., Michalski, R. S., Pietrzykowski, J. and Wojtusiak, J., "An Integrated Multi-task Inductive Database and Decision Support System VINLEN: An initial implementation and first results ," Presented at the 5th International Workshop on Knowledge Discovery in Inductive Databases, KDID'06, in conjunction with ECML/PKDD, Berlin, Germany, September 18, 2006. P 06-10 Wojtusiak, J., Michalski, R. S., Kaufman, K. and Pietrzykowski, J., "The AQ21 Natural Induction Program for Pattern Discovery: Initial Version and its Novel Features," Proceedings of The 18th IEEE International Conference on Tools with Artificial Intelligence, Washington D.C., November 13-15, 2006. P 06-11 Michalski, R. S., Wojtusiak, J. and Kaufman, K., "Intelligent Optimization via Learnable Evolution Model," Proceedings of The 18th IEEE International Conference on Tools with Artificial Intelligence, Washington D.C., November 13-15, 2006. P 06-12 Michalski, R. S., "Optimizing Complex Systems by Intelligent Evolution: The LEMd Method and Case Study," Bulletin of the Polish Academy of Sciences, Technical Sciences, Vol. 54, No. 4, December 2006. P 06-13 Michalski, R. S. and Kaufman, K., "INTELLIGENT EVOLUTIONARY DESIGN: A New Approach to Optimizing Complex Engineering Systems and its Application to Designing Heat Exchangers," International Journal of Intelligent Systems, Volume 21, Issue 12, 2006. 2005 P 05-1 Kaufman, K. and Michalski, R. S., "From Data Mining to Knowledge Mining," Handbook in Statistics, Vol. 24: Data Mining and Data Visualization, Rao, C.R., Solka, J.L. and Wegman, E.J. (Eds.), 47-75, Elsevier/North Holland, 2005. P 05-2 Michalski, R. S. and Wojtusiak, J., "Reasoning with Meta-values in AQ Learning," Reports of the Machine Learning and Inference Laboratory, MLI 05-1, George Mason University, Fairfax, VA, June, 2005. P 05-3 Sniezynski, B., Szymacha, R. and Michalski, R. S., "Knowledge Visualization Using Optimized General Logic Diagrams," Proceedings of the Intelligent Information Processing and Web Mining Conference, IIPWM 05, Gdansk, Poland, June 13-16, 2005. P 05-4 Szydlo, T., Sniezynski, B. and Michalski, R. S., "A Rules-to-Trees Conversion in the Inductive Database System VINLEN," Proceedings of the Intelligent Information Processing and Web Mining Conference, IIPWM 05, Gdansk, Poland, June 13-16, 2005. P 05-5 Wojtusiak, J. and Michalski, R. S., "The LEM3 System for Non-Darwinian Evolutionary Computation and Its Application to Complex Function Optimization," Reports of the Machine Learning and Inference Laboratory, MLI 05-2, George Mason University, Fairfax, VA, October, 2005. P 05-6 Michalski, R. S., Kaufman, K., Pietrzykowski, J., Sniezynski, B. and Wojtusiak, J., "Learning User Models for Computer Intrusion Detection: Preliminary Results from Natural Induction Approach," Reports of the Machine Learning and Inference Laboratory, MLI 05-3, George Mason University, Fairfax, VA, November, 2005. P 05-7 Michalski, R. S. and Wojtusiak, J., "Reasoning with Missing, Not-applicable and Irrelevant Meta-values in Concept Learning and Pattern Discovery," Technical Report 2005-02, Collaborative Research Center 637, University of Bremen, Germany, July 2005. 2004 P 04-1 Domanski, P. A., Yashar, D., Kaufman, K. and Michalski, R. S., "An Optimized Design of Finned-Tube Evaporators Using the Learnable Evolution Model," Reports of the Machine Learning and Inference Laboratory, MLI 04-1, George Mason University, Fairfax, VA, February, 2004. P 04-2 Michalski, R. S., "ATTRIBUTIONAL CALCULUS: A Logic and Representation Language for Natural Induction," Reports of the Machine Learning and Inference Laboratory, MLI 04-2, George Mason University, Fairfax, VA, April, 2004. P 04-3 Maloof, M. and Michalski, R. S., "Incremental Learning with Partial Instance Memory," Artificial Intelligence, 154, 95-126, 2004. P 04-4 Domanski, P. A., Yashar, D., Kaufman, K. and Michalski, R. S., "An Optimized Design of Finned-Tube Evaporators Using the Learnable Evolution Model," International Journal of Heating, Ventilating, Air-Conditioning and Refrigerating Research, 10, 201-211, April, 2004 (a final version of the report 04-1). P 04-5 Wojtusiak, J., "AQ21 User's Guide," Reports of the Machine Learning and Inference Laboratory, MLI 04-3, George Mason University, Fairfax, VA, September, 2004 (updated in September, 2005). P 04-6 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. P 04-7 Wojtusiak, J., "The LEM3 Implementation of Learnable Evolution Model: User's Guide," Reports of the Machine Learning and Inference Laboratory, MLI 04-5, George Mason University, Fairfax, VA, November, 2004. P 04-8 Michalski, R. S., "Generating Alternative Hypotheses in AQ Learning," Reports of the Machine Learning and Inference Laboratory, MLI 04-6, George Mason University, Fairfax, VA, December, 2004. 2003 P 03-1 Kaufman, K. and Michalski, R. S., "The Development of the Inductive Database System VINLEN: A Review of Current Research," International Intelligent Information Processing and Web Mining Conference, Zakopane, Poland, 2003. P 03-2 Cervone, G., Kaufman, K. and Michalski, R. S., "Validating Learnable Evolution Model on Selected Optimization and Design Problems," Reports of the Machine Learning and Inference Laboratory, MLI 03-1, George Mason University, Fairfax, VA, June, 2003. P 03-3 Kaufman, K., Cervone, G. and Michalski, R. S., "An Application of Symbolic Learning to Intrusion Detection: Preliminary Results From the LUS Methodology," Reports of the Machine Learning and Inference Laboratory, MLI 03-2, George Mason University, Fairfax, VA, June, 2003. P 03-4 Michalski, R. S., "Inferential Theory of Learning and Inductive Databases," Invited paper at the UQAM Summer Institute in Cognitive Sciences, Montreal, Canada, June 30-July 11, 2003. P 03-5 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. 2002 P 02-1 Maloof, M. and Michalski, R. S., "Incremental Learning with Partial Instance Memory," Foundations of Intelligent Systems, Lecture Notes in Artificial Intelligence, (Proceedings of the Thirteenth International Symposium on Methodologies for Intelligent Systems, Lyon, France), Vol. 2366, 16-27, Berlin:Springer-Verlag, 2002. P 02-2 Cervone, G., Kaufman, K. and Michalski, R. S., "Recent Results from the Experimental Evaluation of the Learnable Evolution Model," Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2002, 2002. P 02-3 Cervone, G. and Michalski, R. S., "Modeling User Behavior by Integrating AQ Learning with a Database: Initial Results," Proceedings of the IIS-02 Eleventh International Symposium on Intelligent Information Systems, Sopot, Poland, June, 2002. P 02-4 Scorcioni, R., Cervone, G. and Ascoli, G. A., "Machine learning derived rules for the quantitative definition of neuromorphological classes," Program No. 312.15. 2002 Poster Session Washington DC, Society for Neuroscience, 2002. CD-ROM., 10th November 2002. P 02-5 Michalski, R. S., "Attributional Ruletrees: A New Representation for AQ Learning," Reports of the Machine Learning and Inference Laboratory, MLI 02-1, George Mason University, Fairfax, VA, October, 2002 (slightly edited in May, 2004).. 2001 P 01-1 Michalski, R. S. and Kaufman, K., "The AQ19 System for Machine Learning and Pattern Discovery: A General Description and User's Guide," Reports of the Machine Learning and Inference Laboratory, MLI 01-2, George Mason University, Fairfax, VA, 2001. P 01-2 Michalski, R. S. and Cervone, G., "Adaptive Anchoring Discretization for Learnable Evolution Model: The ANCHOR Method," Reports of the Machine Learning and Inference Laboratory, MLI 01-3, George Mason University, Fairfax, VA, 2001. P 01-3 Cervone, G., Panait, L. A. and Michalski, R. S., " The Development of the AQ20 Learning System and Initial Experiments," Tenth International Symposium on Intelligent Information Systems, Zakopane, Poland, June, 2001. P 01-4 Glowinski, C. and Michalski, R. S., "Discovering Multi-head Attributional Rules in Large Databases," Tenth International Symposium on Intelligent Information Systems, Zakopane, Poland, June, 2001. P 01-5 Michalski, R. S., "Attributional Calculus: A Logic and Representation System for Natural Induction--Preliminary Version," Reports of the Machine Learning and Inference Laboratory, MLI 01-1, George Mason University, Fairfax, VA, 2001. (Superseded by Michalski R.S., "ATTRIBUTIONAL CALCULUS: A Logic and Representation System for Natural Induction," Reports of the Machine Learning and Inference Laboratory, MLI 04-2, 2004.) P 01-6 Michalski, R. S. and Kaufman, K., "Learning Patterns in Noisy Data: The AQ Approach," Machine Learning and its Applications, G. Paliouras, V. Karkaletsis and C. Spyropoulos (Eds.), pp. 22-38, Springer-Verlag, 2001. P 01-7 Cervone, G. and Zucchelli, M., "An Application of Machine Learning to the Optimization of Disparity Maps," Proceedings of IASTED-01, 2001. 2000 P 00-1 Publications of the Machine Learning and Inference Laboratory 1988-1999, Reports of the Machine Learning and Inference Laboratory, MLI 00-1, R. S. Michalski and K. Kaufman (Eds.), George Mason University, Fairfax, VA, January, 2000. P 00-2 Michalski, R. S., "LEARNABLE EVOLUTION MODEL Evolutionary Processes Guided by Machine Learning," Machine Learning , Vol. 38, pp. 9-40, 2000. P 00-3 Kaufman, K. and Michalski, R. S., "ISHED1: Applying the LEM Methodology to Heat Exchanger Design," Reports of the Machine Learning and Inference Laboratory, MLI 00-2, George Mason University, Fairfax, VA, 2000. P 00-4 Kaufman, K. and Michalski, R. S., "The AQ18 System for Machine Learning and Data Mining System: An Implementation and User's Guide," Reports of the Machine Learning and Inference Laboratory, MLI 00-3, George Mason University, Fairfax, VA, 2000. P 00-5 Kaufman, K. and Michalski, R. S., "An Adjustable Rule Learner for Pattern Discovery Using the AQ Methodology," Journal of Intelligent Information Systems, 14, pp 199-216, 2000. P 00-6 Michalski, R. S. and Kaufman, K., "Building Knowledge Scouts Using KGL Metalanguage," Fundamenta Informaticae , 40, pp 433-447, 2000. P 00-7 Cervone, G., Michalski, R. S., Kaufman, K. and Panait, L. A., " Combining Machine Learning with Evolutionary Computation Recent Results on LEM," Proceedings of the Fifth International Workshop on Multistrategy Learning (MSL-2000), Guimaraes, Portugal, pp 41-58, June 2000. P 00-8 Michalski, R. S., Cervone, G. and Kaufman, K., " Speeding Up Evolution through Learning: LEM," Proceedings of the Ninth International Symposium on Intelligent Information Systems, Bystra, Poland, June 12-16 2000. P 00-9 Cervone, G., Kaufman, K. and Michalski, R. S., " Experimental Validations of the Learnable Evolution Model," 2000 Congress on Evolutionary Computation, San Diego CA, pp 1064-1071, July 2000. P 00-10 Kaufman, K. and Michalski, R. S., "Applying Learnable Evolution Model to Heat Exchanger Design," Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI-2000) and Twelfth Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-2000), Austin, TX, pp. 1014-1019, 2000. P 00-11 Maloof, M. and Michalski, R. S., "Selecting Examples for Partial Memory Learning," Machine Learning, 41, pp. 27-52, 2000. P 00-12 Kaufman, K. and Michalski, R. S., "A Knowledge Scout for Discovering Medical Patterns: Methodology and System SCAMP," Proceedings of the Fourth International Conference on Flexible Query Answering Systems, FQAS'2000, Warsaw, Poland, pp. 485-496, October 25-28, 2000. P 00-13 Michalski, R. S., "Learning and Evolution: An Introduction to Non-Darwinian Evolutionary Computation," Invited paper, Twelfth International Symposium on Methodologies for Intelligent Systems, Charlotte, NC, 2000. P 00-14 Michalski, R. S. and Brazdil, P. (Eds.), Proceedings of the Fifth International Workshop on Multistrategy Learning (MSL'00), Guimaraes, Portugal, June 11-14, 2000. 1999 P 99-1 An Overview of Research Activities in the Machine Learning and Inference Laboratory: 1998-1999, Reports of the Machine Learning and Inference Laboratory, MLI 99-1, R. S. Michalski and K. Kaufman (Eds.), George Mason University, Fairfax, VA, January, 1999. P 99-2 Kaufman, K. and Michalski, R. S., " Learning in an Inconsistent World: Rule Selection in AQ18," Reports of the Machine Learning and Inference Laboratory, MLI 99-2, George Mason University, Fairfax, VA, May, 1999. P 99-3 Michalski, R. S., "LEARNABLE EVOLUTION MODEL: Evolutionary Processes Guided by Machine Learning," subsumed by ML Journal paper, Reports of the Machine Learning and Inference Laboratory, MLI 99-3, George Mason University, Fairfax, VA, May, 1999. P 99-4 Michalski, R. S. and Zhang, Q., "Initial Experiments with the LEM1 Learnable Evolution Model: An Application to Function Optimization and Evolvable Hardware," Reports of the Machine Learning and Inference Laboratory, MLI 99-4, George Mason University, Fairfax, VA, May 1999. Slightly updated version of report MLI 98-3. P 99-5 Coletti, M., Lash, T., Mandsager, C., 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. P 99-6 Kaufman, K. and Michalski, R. S., "Learning from Inconsistent and Noisy Data: The AQ18 Approach," Proceedings of the Eleventh International Symposium on Methodologies for Intelligent Systems, Warsaw, pp. 411-419, June 8-11. P 99-7 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. P 99-8 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. P 99-9 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. P 99-10 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. P 99-11 Cervone, G., "An Experimental Application of the Learnable Evolution Model to Selected Optimization Problems," Master's Thesis, Department of Computer Science, Reports of the Machine Learning and Inference Laboratory, MLI 99-12, George Mason University, Fairfax, VA, November 1999. 1998 P 98-1 An Overview of Research Activities in the Machine Learning and Inference Laboratory: 1997-1998, Reports of the Machine Learning and Inference Laboratory, MLI 98-1, R. S. Michalski and Q. Zhang (Eds.), George Mason University, Fairfax, VA, January, 1998. P 98-2 Zhang, Q., Duric, Z. 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. P 98-3 Fischthal, S., "Conceptual Clusterer CLUSTER/2C++: An Object-Oriented Design and Code Documentation," Reports of the Machine Learning and Inference Laboratory, MLI 98-2, George Mason University, Fairfax, VA, 1998. P 98-4 Kubat, M., Bratko, I. and Michalski, R. S., "A Review of Machine Learning Methods," Machine Learning and Data Mining: Methods and Applications, R. S. Michalski, I. Bratko and M. Kubat (Eds.), pp. 3-69, London: John Wiley & Sons, 1998. P 98-5 Michalski, R. S. and Kaufman, K., "Data Mining and Knowledge Discovery: A Review of Issues and a Multistrategy Approach," Machine Learning and Data Mining: Methods and Applications, R. S. Michalski, I. Bratko and M. Kubat (Eds.), pp. 71-112, London: John Wiley & Sons, 1998. P 98-6 Michalski, R. S., Rosenfeld, A., Duric, Z., Maloof, M. and Zhang, Q., "Learning Patterns in Images," Machine Learning and Data Mining: Methods and Applications, R. S. Michalski, I. Bratko and M. Kubat (Eds.), London, pp. 241-268, John Wiley & Sons, 1998. P 98-7 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. P 98-8 Bloedorn, E. and Michalski, R. S., "Data-Driven Constructive Induction," IEEE Intelligent Systems, Special issue on Feature Transformation and Subset Selection, pp. 30-37, March/April, 1998. P 98-9 Michalski, R. S., "Learnable Evolution: Combining Symbolic and Evolutionary Learning," Proceedings of the Fourth International Workshop on Multistrategy Learning (MSL'98), Desenzano del Garda, Italy, pp. 14-20, June 11-13, 1998. P 98-10 Kaufman, K. and Michalski, R. S., "Discovery Planning: Multistrategy Learning in Data Mining," Proceedings of the Fourth International Workshop on Multistrategy Learning (MSL'98) , Desenzano del Garda, Italy, June 11-13, 1998. P 98-11 Esposito, F., Michalski, R. S. and Saitta, L. (Eds.), Proceedings of the Fourth International Workshop on Multistrategy Learning (MSL'98), Desenzano del Garda, Italy, June 11-13, 1998. P 98-12 Michalski, R. S. and Kaufman, K., "Multistrategy Data Mining via the KGL Metalanguage," Proceedings of the Seventh Symposium on Intelligent Information Systems (IIS'98) , Malbork, Poland, pp. 39-48, June 15-19, 1998. P 98-13 Michalski, R. S., Bratko, I. and Kubat, M. (Eds.), Machine Learning and Data Mining: Methods and Applications, London, John Wiley & Sons, 1998. 1997 P 97-1 "Publication List of the Machine Learning and Inference Laboratory: 1988-1997," Reports of the Machine Learning and Inference Laboratory, MLI 97-1, George Mason University, Fairfax, VA, 1997. P 97-2 Maloof, M. and Michalski, R. S., "Learning Symbolic Descriptions of Shape for Object Recognition In X-Ray Images," Expert Systems with Applications, Vol. 12(1), pp. 11-20, 1997. P 97-3 Michalski, R. S. and Kaufman, K., "Data Mining and Knowledge Discovery: A Review of Issues and a Multistrategy Approach," Reports of the Machine Learning and Inference Laboratory, MLI 97-2, George Mason University, Fairfax, VA, 1997. P 97-4 Kaufman, K. and Michalski, R. S., "KGL: A Language for Learning," Reports of the Machine Learning and Inference Laboratory, MLI 97-3, George Mason University, Fairfax, VA, 1997. P 97-5 Lee, S. W., Fischthal, S. and Wnek, J., "Using Bayesian Classification for AQ-based Learning with Constructive Induction," Reports of the Machine Learning and Inference Laboratory, MLI 97-4, George Mason University, Fairfax, VA, 1997. P 97-6 Zhang, Q. and Michalski, R. S., "Speeding GA-based Attribute Selection for Image Interpretation," Reports of the Machine Learning and Inference Laboratory, MLI 97-5, George Mason University, Fairfax, VA, 1997. P 97-7 Michalski, R. S. and Imam, I. F., "On Learning Decision Structures," Fundamenta Matematicae, 31(1), dedicated to the memory of Dr. Cecylia Raucher, Polish Academy of Sciences, pp. 49-64, 1997. P 97-8 Ko, H., "Emperical Assembly Sequence Planning: A Multistrategy Constructive Learning Approach," Machine Learning and Data Mining: Methods and Applications, R. S. Michalski, I. Bratko and M. Kubat (Eds.), London, John Wiley & Sons, 1998. P 97-9 Lee, S. W. and Michalski, R. S., "ALPE: A System for Automatic Learning Performance Evaluation The Method and User's Guide," Reports of the Machine Learning and Inference Laboratory, MLI 97-6, George Mason University, Fairfax, VA, 1997. P 97-10 Bloedorn, E. and Michalski, R. S., "Data-Driven Constructive Induction: A Methodology and its Applications," Reports of the Machine Learning and Inference Laboratory, MLI 97-7, George Mason University, Fairfax, VA, 1997. P 97-11 Kaufman, K. and Michalski, R. S., "EMERALD 2: An Integrated System of Machine Learning and Discovery Programs for Education and Research, User's Guide (Updated Edition)," Reports of the Machine Learning and Inference Laboratory, MLI 97-8, George Mason University, Fairfax, VA, 1997. P 97-12 Kaufman, K. and Michalski, R. S., "EMERALD 2: An Integrated System of Machine Learning and Discovery Programs for Education and Research, Programmer's Guide for the Sun Workstation (Updated Edition)," Reports of the Machine Learning and Inference Laboratory, MLI 97-9, George Mason University, Fairfax, VA, 1997. P 97-13 Fischthal, S., "A Description and User's Guide for CLUSTER/2C++ A Program for Conjunctive Conceptual Clustering," Reports of the Machine Learning and Inference Laboratory, MLI 97-10, George Mason University, Fairfax, VA, 1997. P 97-14 An Overview of Research Activities in the Machine Learning and Inference Laboratory: 1996-1997, Reports of the Machine Learning and Inference Laboratory, MLI 97-11, George Mason University, Fairfax, VA, 1997. P 97-15 Michalski, R. S. and Wnek, J. (Eds.), Second Special Issue on Multistrategy Learning, Machine Learning, Vol. 27,No. 3, June 1997. P 97-16 Michalski, R. S. and Kaufman, K., "Multistrategy Data Exploration Using the INLEN System: Recent Advances," Sixth International Conference on Intelligent Information Systems, Zakopane, Poland, June, 1997. P 97-17 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. P 97-18 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. P 97-19 Zhang, Q., "Knowledge Visualizer: A Software System for Visualizing Data, Patterns and Their Relationships," Reports of the Machine Learning and Inference Laboratory , MLI 97-14, George Mason University, Fairfax, VA, September, 1997. P 97-21 Michalski, R. S., "Seeking Knowledge in the Deluge of Facts," Fundamenta Informaticae, Vol. 30, pp. 283-297, 1997. P 97-22 Kaufman, K., "INLEN: A Methodology and Integrated System for Knowledge Discovery in Databases," Ph.D. Dissertation, School of Information Technology and Engineering, Reports of the Machine Learning and Inference Laboratory, MLI 97-15, George Mason University, Fairfax, VA, November, 1997. P 97-23 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. 1996 P 96-1 "Machine Learning and Inference Laboratory: An Overview of Research and Activities," Reports of the Machine Learning and Inference Laboratory, MLI 96-1, George Mason University, Fairfax, VA, January 1996. P 96-2 "Publication List of Machine Learning and Inference Laboratory Part 1: 1969-1987," MLI 96-2, George Mason University, Fairfax, VA, January 1996. P 96-3 "Publication List of Machine Learning and Inference Laboratory 2: 1988-1995," MLI 96-3, George Mason University, Fairfax, VA, January 1996. P 96-4 Kaufman, K. and Michalski, R. S., "A Multistrategy Conceptual Analysis of Economic Data," Artificial Intelligence in Economics and Management: An Edited Proceedings on the Fourth International Workshop, Boston, pp. 193-203, Kluwer Academic Publishers, 1996. P 96-5 Michalski, R. S., Rosenfeld, A., Aloimonos, Y., Duric, Z., Maloof, M. and Zhang, Q., "Progress On Vision Through Learning: A Collaborative Effort of George Mason University and University of Maryland," Proceedings of the Image Understanding Workshop, Palm Springs, CA, Feburary, 1996. P 96-7 Michalski, R. S., Zhang, J., Maloof, M. and Bloedorn, E., "The MIST Methodology and its Application to Natural Scene Interpretation," Proceedings of the Image Understanding Workshop, Palm Springs, CA, pp. 1473-1479, Feburary, 1996. P 96-8 Duric, Z., Rivlin, E. and Rosenfeld, A., "Learning an Object's Function by Observing the Object in Action," Proceedings of the Image Understanding Workshop, Palm Springs, CA, February, 1996. P 96-9 Maloof, M., Duric, Z., Michalski, R. S. and Rosenfeld, A., "Recognizing Blasting Caps in X-Ray Images," Proceedings of the Image Understanding Workshop, Palm Springs, CA, Feburary, 1996. P 96-10 Imam, I., "The AQDT-2 USER'S GUIDE: A Machine Learning Program for Learning Task-oriented Decision Structures from Decision Rules," Reports of the Machine Learning and Inference Laboratory, MLI 96-4, George Mason University, Fairfax, VA, March 1996. P 96-11 Imam, I., "The AQDT-2 PROGRAMMER'S GUIDE: A Machine Learning Program for Learning Task-oriented Decision Structures from Decision Rules," Reports of the Machine Learning and Inference Laboratory, MLI 96-5, George Mason University, Fairfax, VA, March 1996. P 96-12 Michalski, R. S. and Wnek, J. (Eds.), Proceedings of the Third International Workshop on Multistrategy Learning (MSL-96), Harpers Ferry, WV, May 23-25, 1996. P 96-13 Alkharouf, N. W. and Michalski, R. S., "Multistrategy Task-Adaptive Learning Using Dynamic Interlaced Hierarchies: A Methodology and Initial Implementation of INTERLACE," Proceedings of the Third International Workshop on Multistrategy Learning (MSL-96), Harpers Ferry, WV, pp. 117-124, May 23-25, 1996. P 96-14 Kaufman, K., "Addressing Knowledge Discovery Problems in a Multistrategy Framework," Proceedings of the Third International Workshop on Multistrategy Learning (MSL-96), Harpers Ferry, WV, pp. 305-312, May 23-25, 1996. P 96-15 Bloedorn, E. and Michalski, R. S., "The AQ17-DCI System for Data-Driven Constructive Induction and Its Application to the Analysis of World Economics," Proceedings of the Ninth International Symposium on Methodologies for Intelligent Systems (ISMIS-96), Zakopane, Poland, June 10-13, 1996. P 96-16 Imam, I. and Michalski, R. S., "An Empirical Comparison Between Learning Decision Trees from Examples and from Decision Rules," Proceedings of the Ninth International Symposium on Methodologies for Intelligent Systems (ISMIS-96), Zakopane, Poland, June 10-13. P 96-17 Imam, I., "Do We Efficiently Estimate the Attributional Relevancy to Learning Systems?," Proceedings of the Ninth International Symposium on Methodologies for Intelligent Systems (ISMIS-96), Zakopane, Poland, June 10-13, 1996. P 96-18 Duric, Z., Fayman, J. A. and Rivlin, E., "Function From Motion," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 18, No. 6, pp. 579-591, June, 1996. P 96-19 Wnek, J., Kaufman, K., Bloedorn, E. and Michalski, R. S., "Inductive Learning System AQ15c: The Method and User's Guide," Reports of the Machine Learning and Inference Laboratory, MLI 96-6, George Mason University, Fairfax, VA, August, 1996. P 96-20 Bloedorn, E., Mani, I. and MacMillan, T. R., "Machine Learning of User Profiles: Representational Issues," Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), Portland, OR, August, 1996. P 96-21 Kaufman, K. and Michalski, R. S., "A Method for Reasoning with Structured and Continuous Attributes in the INLEN-2 Multistrategy Knowledge Discovery System," Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96), Portland, OR, pp. 232-237, August, 1996. P 96-22 Duric, Z. and Rosenfeld, A., "Image Sequence Stabilization in Real Time," Real-Time Imaging, Vol. 2, pp. 271-284, 1996. P 96-23 Bloedorn, E., "Multistrategy Constructive Induction," Ph.D. Dissertation,Reports of the Machine Learning and Inference Laboratory, MLI 96-7, School of Information Technology and Engineering,George Mason University, Fairfax, VA, 1996. P 96-24 Maloof, M. and Michalski, R. S., "Partial Memory Learning System AQ-PM: The Method and User's Guide," Reports of the Machine Learning and Inference Laboratory, MLI 96-8, George Mason University, Fairfax, VA, 1996. P 96-25 Maloof, M., "Progressive Partial Memory Learning," Ph.D. Dissertation, Reports of the Machine Learning and Inference Laboratory, MLI 96-9, School of Information Technology and Engineering, George Mason University, Fairfax, VA, 1996. P 96-26 Lee, S. W., "Multistrategy Learning: An Empirical Study with AQ + Bayesian Approach," Reports of the Machine Learning and Inference Laboratory, MLI 96-10, George Mason University, Fairfax, VA, 1996. P 96-27 Lee, S. W., "WWW-AQ: World Wide Web Interface for the AQ Learning System Users and Programmers Guide," Reports of the Machine Learning and Inference Laboratory, MLI 96-11, George Mason University, Fairfax, VA, 1996. P 96-28 Zhang, Q., Duric, Z. and Michalski, R. S., "Target Detection in SAR Images Using the MIST/AQ Method," Reports of the Machine Learning and Inference Laboratory, MLI 96-12, George Mason University, Fairfax, VA, 1996. 1995 P 95-1 "Center for Machine Learning and Inference: An Overview of Research and Activities," Reports of the Machine Learning and Inference Laboratory, MLI 95-1, George Mason University, Fairfax, VA, January, 1995. P 95-2 Maloof, M. and Michalski, R. S., "A Partial Memory Incremental Learning Methodology and its Application to Computer Intrusion Detection," Reports of the Machine Learning and Inference Laboratory, MLI 95-2, George Mason University, Fairfax, VA, March 1995. P 95-3 Bloedorn, E., Imam, I., Kaufman, K., Maloof, M., Michalski, R. S. and Wnek, J., "HOW DID AQ FACE THE EAST-WEST CHALLENGE? An Analysis of the AQ Family's Performance in the 2nd International Competition of Machine Learning Programs," Reports of the Machine Learning and Inference Laboratory, MLI 95-3, George Mason University, Fairfax, VA, March 1995. P 95-4 Wnek, J., Kaufman, K., Bloedorn, E. and Michalski, R. S., "Inductive Learning System AQ15c: The Method and User's Guide," Reports of the Machine Learning and Inference Laboratory, MLI 95-4, George Mason University, Fairfax, VA, March 1995. P 95-5 Wnek, J., "DIAV 2.0 User Manual: Specification and Guide through the Diagrammatic Visualization System," Reports of the Machine Learning and Inference Laboratory, MLI 95-5, George Mason University, Fairfax, VA, 1995. P 95-6 Arciszewski, T., Michalski, R. S. and Dybala, T., "STAR Methodology-Based Learning about Construction Accidents and their Prevention," Journal of Construction Automation, Vol. 4, pp. 75-85, 1995. P 95-7 "Proceedings of the First International Workshop on Intelligent Adaptive Systems (IAS-95)," , I. Imam and J. Wnek (Eds.), Melbourne Beach, FL, April 26, 1995. P 95-8 Bloedorn, E. and Wnek, J., "Constructive Induction-based Learning Agents: An Architecture and Preliminary Experiments," Proceedings of the First International Workshop on Intelligent Adaptive Systems (IAS-95), Melbourne Beach, FL, pp. 38-49, April 26, 1995. P 95-9 Imam, I., "Intelligent Agents for Management of Learning: An Introduction and a Case Study," Proceedings of the First International Workshop on Intelligent Adaptive Systems (IAS-95), Melbourne Beach, FL, pp. 95-106, April 26, 1995. P 95-10 Arciszewski, T., Michalski, R. S. and Wnek, J., "Constructive Induction: The Key to Design Creativity," Reports of the Machine Learning and Inference Laboratory, MLI 95-6, Machine Learning and Inference Laboratory, George Mason University, Fairfax, VA, April 1995. P 95-11 Chen, Q. and Arciszewski, T., "Machine Learning of Bridge Design Rules: A Case Study," Proceedings of the 2nd ASCE Congress on Computing in Civil Engineering, Atlanta GA, June, 1995. P 95-12 Ribeiro, J., Kaufman, K. and Kerschberg, L., "Knowledge Discovery from Multiple Databases," Proceedings of the IASTED/ISMM International Conference on Intelligent Information Management Systems, Washington, D.C., June, 1995. P 95-13 Michalski, R. S. and Wnek, J., "Learning Hybrid Descriptions," Proceedings of the 4th International Symposium on Intelligent Information Systems, Augustow, Poland, June 5-9, 1995. P 95-14 Michalski, R. S., "Learning and Cognition," Invited talk at 2nd International World Conference on the Foundations of Artificial Intelligence, Paris, July 3-7, 1995. P 95-15 Szczepanik, W., Arciszewski, T. and Wnek, J., "Empirical Performance Comparison of Two Symbolic Learning Systems Based On Selective And Constructive Induction," Proceedings of the IJCAI-95 Workshop on Machine Learning in Engineering, Montreal, Canada, August, 1995. P 95-16 Ribeiro, J., Kaufman, K. and Kerschberg, L., "Knowledge Discovery from Multiple Databases," Proceedings of the First International Conference on Knowledge Discovery and Data Mining (KDD-95), Montreal, Canada, pp. 240-245, August, 1995. P 95-17 Maloof, M. and Michalski, R. S., "Learning Symbolic Descriptions of 2D Shapes for Object Recognition in X-ray Images," Proceedings of the 8th International Symposium on Artificial Intelligence, Monterrey, Mexico, October 17-20, 1995. P 95-18 Maloof, M. and Michalski, R. S., "A Method for Partial-Memory Incremental Learning and its Application to Computer Intrusion Detection," Proceedings of the 7th IEEE International Conference on Tools with Artificial Intelligence, Herndon, VA, 1995. P 95-19 De Jong, K. and Vafaie, H., "Genetic Algorithm as a Tool for Restructuring Feature Space Representations," Proceedings of the 7th IEEE International Conference on Tools with Artificial Intelligence, Herndon, VA, 1995. P 95-20 Imam, I., "Deriving Task-oriented Decision Structures From Decision Rules," Ph.D. dissertation School of Information Technology and Engineering, Reports of the Machine Learning and Inference Laboratory, MLI 95-7, George Mason University, Fairfax, VA, October 1995. P 95-21 Michalski, R. S. and Ram, A., "Learning as Goal-Driven Inference," Goal-Driven Learning, A. Ram and D. B Leake (Eds.), MIT Press/Bradford Books P 95-22 Maloof, M. and Michalski, R. S., "Learning Evolving Concepts Using Partial Memory Approach," Proceedings of the AAAI 1995 Fall Symposium on Active Learning, Cambridge, MA, November 10-12, 1995. P 95-23 Arciszewski, T., Michalski, R. S. and Wnek, J., "Constructive Induction: the Key to Design Creativity," Proceedings of the Third International Round-Table Conference on Computational Models of Creative Design, Heron Island, Queensland, Australia, pp. 397-425, December 3-7, 1995. P 95-24 Zhang, J. and Michalski, R. S., "An Integration of Rule Induction and Exemplar- Based Learning for Graded Concepts," Machine Learning, Vol.21, No.3, pp. 235-268, Kluwer Academic Publishers, December 1995. P 95-25 "Presentation Notes of the Annual Review of Research in Machine Learning and Inference," , J. Wnek and R. S. Michalski (Eds.), Machine Learning and Inference Laboratory, George Mason University, Fairfax, VA, May 19, 1995. P 95-26 Arciszewski, T., Bloedorn, E., Michalski, R. S., Mustafa, M. and Wnek, J., "Machine Learning in Engineering Design: A Methodology and Case Study," Reports of the Machine Learning and Inference Laboratory, MLI 95-8, George Mason University, Fairfax, VA, December, 1995. 1994 P 94-1 Michalski, R. S. and Tecuci, G. (Eds.), Machine Learning -A Multistrategy Approach Vol IV, San Mateo, CA., Morgan Kaufmann, 1994. P 94-2 Bala, J. W., De Jong, K. A. and Pachowicz, P. W., "Multistrategy Learning from Engineering Data by Integrating Inductive Generalization and Genetic Algorithms," Machine Learning: A Multistrategy Approach, Vol. IV, San Mateo, CA, 471-488, Morgan Kaufmann, 1994. P 94-3 De Garis, H., "Genetic Programming: Evolutionary Approaches to Multistrategy Learning," Machine Learning: A Multistrategy Approach, Vol. IV, San Mateo, CA, 549-578, Morgan Kaufmann, 1994. P 94-4 Michalski, R. S., "Inferential Theory of Learning: Developing Foundations for Multistrategy Learning," Machine Learning: A Multistrategy Approach, Vol. IV, San Mateo, CA, pp. 3-61, Morgan Kaufmann, 1994. P 94-5 Vafaie, H. and De Jong, K. A., "Improving the Performance of a Rule Induction System Using Genetic Algorithms," Machine Learning: A Multistrategy Approach, Vol. IV, San Mateo, CA, 453-470, Morgan Kaufmann, 1994. P 94-6 Wnek, J. and Michalski, R. S., "Comparing Symbolic and Subsymbolic Learning: Three Studies," Machine Learning: A Multistrategy Approach, Vol. IV, R. S. Michalski and G. Tecuci (Eds.), San Mateo, CA, 489-519, Morgan Kaufmann, 1994. P 94-7 Wnek, J. and Hieb, M. R., "Bibliography of Multistrategy Learning Research," Machine Learning: A Multistrategy Approach, Vol. IV, San Mateo, CA, 657-730, Morgan Kaufmann, 1994. P 94-8 Zhang, J., "Learning Graded Concept Descriptions by Integrating Symbolic and Subsymbolic Approaches," Machine Learning: A Multistrategy Approach, Vol. IV, R. S. Michalski and G. Tecuci (Eds.), San Mateo, CA, 431-452, Morgan Kaufmann, 1994. P 94-9 Wnek, J. and Michalski, R. S., "Hypothesis-driven Constructive Induction in AQ17-HCI: A Method and Experiments," Machine Learning, Vol. 14, No. 2, pp. 139-168, 1994. P 94-10 Vafaie, H. and Imam, I., "Feature Selection Methods: Genetic Algorithm vs. Greedy-like Search," Proceedings of the 3rd International Fuzzy Systems and Intelligent Control Conference, Louisville, KY, March 1994. P 94-11 Wnek, J. and Michalski, R. S., "Symbolic Learning of M-of-N Concepts," Reports of the Machine Learning and Inference Laboratory, MLI 94-1, School of Information Technology and Engineering, George Mason University, Fairfax, VA, April 1994. P 94-12 Bloedorn, E., Michalski, R. S. and Wnek, J., "Matching Methods with Problems: A Comparative Analysis of Constructive Induction Approaches," Reports of the Machine Learning and Inference Laboratory, MLI 94-2, School of Information Technology and Engineering, George Mason University, Fairfax, VA, May 1994. P 94-13 Imam, I. and Vafaie, H., "An Empirical Comparison Between Global and Greedy-like Search for Feature Selection," Proceedings of the 7th Florida Artificial Intelligence Research Symposium (FLAIRS-94), Pensacola Beach, FL, pp. 66-70, May 1994. P 94-14 Tischer, L. and Bloedorn, E., "An Application of Machine Learning to GIS Analysis," Proceedings of the ESRI-94 User Conference, CA, May 1994. P 94-15 Imam, I., "An Experimental Study of Discovery in Large Temporal Databases," Proceedings of the Seventh International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE-94), Austin, TX, pp. 171-180, June 1994. P 94-16 Arciszewski, T., Bloedorn, E., Michalski, R. S., Mustafa, M. and Wnek, J., "Machine Learning of Design Rules: Methodology and Case Study," ASCE Journal of Computing in Civil Engineering, Vol. 8, No. 3, pp. 286-308, July 1994. P 94-17 Sazonov, V. N. and Wnek, J., "Hypothesis-driven Constructive Induction Approach to Expanding Neural Networks," Working Notes of the ML-COLT'94 Workshop on Constructive Induction and Change of Representation, New Brunswick, NJ, July 1994. P 94-18 Wnek, J. and Michalski, R. S., "Discovering Representation Space Transformations for Learning Concept Descriptions Combining DNF and M-of-N Rules," Working Notes of the ML-COLT'94 Workshop on Constructive Induction and Change of Representation, New Brunswick, NJ, July 1994. P 94-19 Arciszewski, T., Khasnabis, S., Hoda, S. K. and Ziarko, W., "Machine Learning in Transportation Engineering: A Feasibility Study," Journal of Applied Artificial Intelligence, Vol. 8, No. 1, 1994. P 94-20 Arciszewski, T., Borkowski, A., Dybala, T., Racz, J. and Wojan, P., "Empirical Comparison for Symbolic and Subsymbolic Learning Systems," Proceedings of the First International ASCE Congress on Computing in Civil Engineering, Washington, D.C., 1994. P 94-21 Arciszewski, T., "Machine Learning in Engineering Design," Proceedings of the Conference on Intelligent Information Systems, Institute of Computer Science, Polish Academy of Sciences, Wigry, Poland, 1994. P 94-22 Arciszewski, T. and Michalski, R. S., "Inferential Design Theory: A Conceptual Outline," Proceedings of the Third International Conference on Artificial Intelligence in Design, Lausanne, Switzerland, 1994. P 94-23 Imam, I. and Michalski, R. S., "From Fact to Rules to Decisions: An Overview of the FRD-1 System," Proceedings of the AAAI-94 Workshop on Knowledge Discovery in Databases, Seattle, WA, pp. 229-236, August, 1994. P 94-24 Kaufman, K., "Comparing International Development Patterns Using Multi-operator Learning and Discovery Tools," Proceedings of the AAAI-94 Workshop on Knowledge Discovery in Databases, Seattle, WA, pp. 431-440, August, 1994. P 94-25 Maloof, M. and Michalski, R. S., "Learning Descriptions of 2D Shapes for Object Recognition and X-Ray Images," Reports of the Machine Learning and Inference Laboratory, MLI 94-4, George Mason University, Fairfax, VA, October 1994. P 94-26 Michalski, R. S. and Ram, A., "Learning as Goal-Driven Inference," Reports of the Machine Learning and Inference Laboratory, MLI 94-5, George Mason University, Fairfax, VA, October 1994. P 94-27 Michalski, R. S., Rosenfeld, A. and Aloimonos, Y., "Machine Vision and Learning: Research Issues and Directions," Reports of the Machine Learning and Inference Laboratory, Reports of the Center for Automation Research CAR-TR-739, MLI 94-6, CS-TR-3358, George Mason University, Fairfax, VA, University of Maryland, College Park, MD, October 1994. P 94-28 Michalski, R. S. and Imam, I., "Learning Problem-Oriented Decision Structures from Decision Rules: The AQDT-2 System," Lecture Notes in Artificial Intelligence, Methodology for Intelligent Systems of the 8th International Symposium on Methodology for Intelligent Systems (ISMIS-94), No. 869, pp. 416-426, October, 1994. P 94-29 Michaels, G. S., "Bioinformatics or Biology?," Chemical Design Automation News, Vol. 8, pp. 1-34, 1994. P 94-30 Michaels, G. S., Taylor, R., Zull, J. E. and Rushforth, N., "Nucleic Acid Sequences Coding for Internal Antisence Peptides: Are There Implications for Protein Folding and Evolution?," Nucleic Acid Research, 1994. P 94-31 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. P 94-32 Michalski, R. S., "Seeking Knowledge in the Flood of Facts," Proceedings of the Conference on Intelligent Information Systems, Institute of Computer Science, Polish Academy of Sciences, Wigry, Poland, pp. 85-102, 1994. P 94-33 Pachowicz, P. W. and Bala, J. W., "A Noise-Tolerant Approach to Symbolic Learning from Sensory Data," Journal of Intelligent and Fuzzy Systems, Vol. 2, pp. 347-361, John Wiley & Sons, Inc., 1994. P 94-34 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. 1993 P 93-1 Michalski, R. S., "Toward a Unified Theory of Learning: Multistrategy Task-adaptive Learning," Readings in Knowledge Acquisition and Learning: Automating the Construction and Improvement of Expert Systems, B. G. Buchanan and D. C. Wikins (Eds.), San Mateo, CA, Morgan Kaufmann, 1993. P 93-2 Michalski, R. S., "A Theory and Methodology of Inductive Learning," Readings in Knowledge Acquisition and Learning: Automating the Construction and Improvement of Expert Systems, B. G. Buchanan and D. C. Wikins (Eds.), San Mateo, CA, Morgan Kaufmann, 1993. P 93-3 Van Mechelen, I., Hampton, J., Michalski, R. S. and Theuns, P. (Eds.), Categories and Concepts: Theoretical Views and Inductive Data Analysis, New York, Academic Press, 1993. P 93-4 Michalski, R. S., "Beyond Prototypes and Frames: The Two-tiered Concept Representation," Categories and Concepts: Theoretical Views and Inductive Data Analysis, I. Van Mechelen, J. Hampton, R. S. Michalski and P. Theuns (Eds.), New York, Academic Press, 1993. P 93-5 Michalski, R. S., "Learning = Inferencing + Memorizing: Basic Concepts of Inferential Theory of Learning and Their Use for Classifying Learning Processes," Foundations of Knowledge Acquisition, Vol. 2: Machine Learning, pp. 1-41, 1993. P 93-6 Bergadano, F., Matwin, S., 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. P 93-7 Michalski, R. S., Pachowicz, P. W., Rosenfeld, A. and Aloimonos, Y., "Machine Learning and Vision: Research Issues and Promising Directions," NSF/DARPA Workshop on Machine Learning and Vision (MLV-92), HarpersFerry, WV, October 15-17, 1992; Reports of the Machine Learning and Inference Laboratory, MLI 93-1, School of Information Technology and Engineering, George Mason University, February, 1993. P 93-8 Wnek, J., "Hypothesis-driven Constructive Induction," Ph.D. dissertation, Reports of the Machine Learning and Inference Laboratory, MLI 93-2, School of Information Technology and Engineering, George Mason University, March 1993. P 93-9 Bala, J. W., "Learning to Recognize Visual Concepts: Development and Implementation of a Method for Texture Concept Acquisition Through Inductive Learning," Ph.D. dissertation, Reports of the Machine Learning and Inference Laboratory, MLI 93-3, School of Information Technology and Engineering, George Mason University, March 1993. P 93-10 Michalski, R. S., Bala, J. W. and Pachowicz, P. W., "GMU Research on Learning in Vision: Initial Results," Proceedings of the DARPA Image Understanding Workshop, Washington D.C., April 18-21, 1993. P 93-11 Bloedorn, E., Wnek, J. and Michalski, R. S., "Multistrategy Constructive Induction: AQ17-MCI," Reports of the Machine Learning and Inference Laboratory, MLI 93-4, School of Information Technology and Engineering, George Mason University, May 1993. P 93-12 Hieb, M. R. and Michalski, R. S., "A Knowledge Representation System Based on Dynamically Interlaced Hierarchies: Basic Ideas and Examples," Reports of the Machine Learning and Inference Laboratory, MLI 93-5, School of Information Technology and Engineering, George Mason University, May 1993. P 93-13 Bloedorn, E., Michalski, R. S. and Wnek, J., "Multistrategy Constructive Induction: AQ17-MCI," Proceedings of the Second International Workshop on Multistrategy Learning (MSL93), Harpers Ferry, WV, pp. 188-203, Morgan Kaufmann, May 26-29, 1993. P 93-14 Hieb, M. R. and Michalski, R. S., "Multitype Inference in Multistrategy Task-adaptive Learning: Dynamic Interlaced Hierarchies," Proceedings of the Second International Workshop on Multistrategy Learning (MSL93), Harpers Ferry, WV, 3-18, Morgan Kaufmann, May 26-29, 1993. P 93-15 Michalski, R. S. and Tecuci, G. (Eds.), Proceedings of the 2nd International Workshop on Multistrategy Learning (MSL93), Harpers Ferry, WV, Morgan Kaufmann, May 26-29, 1993. P 93-16 Imam, I. and Michalski, R. S., "Learning Decision Trees from Decision Rules: A Method and Initial Results from a Comparative Study," Reports of the Machine Learning and Inference Laboratory, MLI 93-6, School of Information Technology and Engineering, George Mason University, May 1993. P 93-17 Wnek, J., Michalski, R. S. and Arciszewski, T., "An Application of Constructive Induction to Engineering Design," Reports of the Machine Learning and Inference Laboratory, MLI 93-7, School of Information Technology and Engineering, George Mason University, May 1993. P 93-18 Imam, I. and Michalski, R. S., "Should Decision Trees Be Learned from Examples or from Decision Rules?," Lecture Notes in Artificial Intelligence, Proceedings of the 7th International Symposium on Methodologies for Intelligent Systems, ISMIS, Trondheim, Norway, Springer Verlag, June 15-18, 1993. P 93-19 Imam, I., Michalski, R. S. and Kerschberg, L., "Discovering Attribute Dependence in Databases by Integrating Symbolic Learning and Statistical Analysis Techniques," Proceedings of the AAAI-93 Workshop on Knowledge Discovery in Databases, Washington, D.C., July 11-12, 1993. P 93-20 Michalski, R. S. and Tecuci, G., "Multistrategy Learning," Tutorial at the National Conference on Artificial Intelligence, AAAI-93, Washington D.C., July 11-12, 1993. P 93-21 Michalski, R. S., "Inferential Theory of Learning as a Conceptual Basis for Multistrategy Learning," Machine Learning, Special Issue on Multistrategy Learning, Vol. 11, pp. 111-151, 1993. P 93-22 Wnek, J., Michalski, R. S. and Arciszewski, T., "An Application of Constructive Induction to Engineering Design," Proceedings of the IJCAI-93 Workshop on AI in Design, Chambery France, August 1993. P 93-23 Michalski, R. S. and Tecuci, G., "Multistrategy Learning," Tutorial at the International Joint Conference on Artificial Intelligence, IJCAI-93, Chambery, France, August, 1993. P 93-24 Kaufman, K., Michalski, R. S. and Schultz, A., "EMERALD 2 An Integrated System of Machine Learning and Discovery Programs for Education and Research User's Guide," Reports of the Machine Learning and Inference Laboratory, MLI 93-8, School of Information Technology and Engineering, George Mason University, Fairfax, VA, September ,1993. P 93-25 Kaufman, K., Schultz, A. and Michalski, R. S., "EMERALD 2 An Integrated System of Machine Learning and Discovery Programs for Education and Research Programmers Guide for the SUN Workstation," Reports of the Machine Learning and Inference Laboratory, MLI 93-9, School of Information Technology and Engineering, George Mason University, Fairfax, VA, September, 1993. P 93-26 Kaufman, K. and Michalski, R. S., "EMERALD 2: An Integrated System of Machine Learning and Discovery Programs to Support Education and Experimental Research," Reports of the Machine Learning and Inference Laboratory, MLI 93-10, School of Information Technology and Engineering, George Mason University, Fairfax, VA, September, 1993. P 93-27 Bala, J. W., Michalski, R. S. and Wnek, J., "The PRAX Approach to Learning a Large Number of Texture Concepts," American Association for Artificial Intelligence(AAAI) Fall Symposium on Machine Learning in Computer Vision, Menlo Park, CA, AAAI Press, October, 1993. P 93-28 Bala, J. W. and Pachowicz, P. W., "Issues in Learning from Noisy Sensory Data," Technical Report FS-93-04 Machine Learning in Computer Vision What Why and How AAAI Fall Symposium on Machine Learning in Computer Vision, Menlo Park, CA, AAAI Press, October 1993. P 93-29 Pachowicz, P. W., "Integration of Machine Learning and Vision into an Active Agent Paradigm on the Example of Face Recognition Problem," Technical Report FS-93-04 Machine Learning in Computer Vision What Why and How AAAI Fall Symposium on Machine Learning in Computer Vision, Menlo Park, CA, AAAI Press, October 1993. P 93-30 Imam, I. and Michalski, R. S., "Learning Decision Trees from Decision Rules A Method and Initial Results from a Comparative Study," Journal of Intelligent Information Systems JIIS, Vol. 2 No. 3, pp 279-304, 1993. P 93-31 Vafaie, H. and De Jong, K. A., "Robust Feature Selection Algorithms," Proceedings of the 5th International Conference on Tools with Artificial Intelligence, Boston, MA, November, 1993. P 93-32 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. P 93-33 Bloedorn, E., Wnek, J., Michalski, R. S. and Kaufman, K., "AQ17 A Multistrategy Learning System The Method and Users Guide," Reports of the Machine Learning and Inference Laboratory, MLI 93-12, School of Information Technology and Engineering, George Mason University, Fairfax, VA, November, 1993. P 93-34 Guillen, Jr., L. E. and Wnek, J., "Investigation of Hypothesis-driven Constructive Induction in AQ17," Reports of the Machine Learning and Inference Laboratory, MLI 93-13, School of Information Technology and Engineering, George Mason University, Fairfax, VA, December 1993. P 93-35 Hieb, M. R. and Michalski, R. S., "Multitype Inference in Multistrategy Task-adaptive Learning Dynamic Interlaced Hierarchies," Informatica: An International Journal of Computing and Informatics, Vol 17 No 4, pp 399-412, December, 1993. P 93-36 Tecuci, G. and Michalski, R. S., "Multistrategy Learning," Encyclopedia of Microcomputers, Vol 12, New York, Marcel Dekker, 1993. P 93-37 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. P 93-38 Khasnabis, S., Arciszewski, T., Hoda, S. K. and Ziarko, W., "Automated Knowledge Acquisition for Control of an Urban Rail Corridor," Proceedings of the Third International Conference on the Applications of Artificial Intelligence to Civil and Structural Engineering, Edinburgh, Scotland, 1993. P 93-39 Arciszewski, T. and Usmen, M., "Applications of Machine Learning to Construction Safety," Proceedings of the International Conference on Management of Information Technology for Construction, Singapore, 1993. P 93-40 Arciszewski, T., Ziarko, W. and Khan, T. L., "Learning Conceptual Design Rules A Rough Sets Approach," Proceedings of the International Workshop on Rough Sets, Banff, Alberta, Canada, 1993. P 93-41 Arciszewski, T., "Learning Engineering An Outline," Proceedings of the ASCE Conference on Computing in Civil Engineering, Anaheim, California, 1993. P 93-42 Seligman, L. and Kerschberg, L., "An Active Database Approach to Consistency Management in Heterogeneous Data-and Knowledge-based Systems," International Journal of Cooperative and Intelligent Systems, Vol 2 No 2, October 1993. P 93-43 Seligman, L. and Kerschberg, L., "Federated Knowledge and Database Systems A New Architecture for Integrating of AI and Database Systems," Advances in Databases and Artificial Intelligence, L. Delcambre and F. Petry (Eds.), Vol 1 The Landscape of Intelligence in Database and Information Systems, JAI Press, 1993. P 93-44 Yoon, J. P. and Kerschberg, L., "A Framework for Knowledge Discovery and Evolution in Databases," IEEE Transactions on Knowledge and Data Engineering, Vol 5 No 6, December 1993. P 93-45 Michalski, R. S., Carbonell, T. J., Mitchell, T. M. and Kodratoff, Y. (Eds.), Apprentissage Symbolique Une Approche de lIntelligence Artificielle Tome I-II French compilation of Machine Learning An Artificial Intelligence Approach, Vol I-III, Cepadues-Editions, 1993. P 93-46 Michalski, R. S. (Ed.), Multistrategy Learning, Kluwer Academic Publishers, 1993. P 93-47 Michaels, G. S., Taylor, R., Hagstrom, R., Price, M. and Overback, R., "Searching for Genomic Organizational Motifs Explorations of the E coli Chromosome," Computers in Chemistry, Vol 17, pp209-217, 1993. P 93-48 Michaels, G. S., Taylor, R., Hagstrom, R., Price, M. and Overback, R., "Comparative Analysis of Genomic Data A Global Look and Structural and Regulatory Features," Proceedings of the Second International Conference of Bioinformatics Supercomputing and Complex Genome Analysis, H. A Lim (Ed.), River Edge, NJ, pp 297-308, World Scientific Publishing Co, 1993. 1992 P 92-1 Bergadano, F., Matwin, S., Michalski, R. S. and Zhang, J., "Learning Two-tiered Descriptions of Flexible Concepts: The POSEIDON System," Machine Learning, Vol. 8, No. 1, pp. 5-43, January, 1992. P 92-2 Wnek, J., "Version Space Transformation with Constructive Induction: The VS* Algorithm," Reports of the Machine Learning and Inference Laboratory, MLI 92-1, George Mason University, Fairfax, VA, January 1992. P 92-3 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. P 92-4 De Jong, K. A. and Spears, W., "A Formal Analysis of the Role of Multi-point Crossover in Genetic Algorithms," Annals of Mathematics and Artificial Intelligence, Vol. 5, No. 1, January, 1992. P 92-5 Fermanian, T. and Michalski, R. S., "AgAssistant: A New Generation Tool for Developing Agricultural Advisory Systems,in Mann," Expert Systems in the Developing Countries: Practice and Promise, Westview Press Publication, 1992. P 92-6 Michalski, R. S. and Chilausky, R., "Knowledge Acquisition by Encoding Expert Rules versus Computer Induction from Examples: A Case Study Involving Soybean Pathology," Artificial Intelligence and Software Engineering, Alex Publishing Corporation, 1992. P 92-7 Michalski, R. S., Kerschberg, L., Kaufman, K. and Ribeiro, J., "Searching for Knowledge in Large Databases," Proceedings of the First International Conference on Expert Systems and Development, Cairo Egypt, April, 1992. P 92-8 Bala, J. W., Michalski, R. S. and Wnek, J., "The Principal Axes Method for Constructive Induction," Proceedings of the 9th International Conference on Machine Learning, Aberdeen, Scotland, July, 1992. P 92-9 Tecuci, G., "Cooperation in Knowledge Base Refinement," Proceedings of the Ninth International Machine Learning Conference (ML92), Aberdeen, Scotland, Morgan Kaufmann, July 1992. P 92-10 Tecuci, G. and Hieb, M. R., "Consistency Driven Knowledge Elicitation Within a Learning Oriented Representation of Knowledge," Proceedings of the AAAI-92 Workshop on Knowledge Representation Aspects of Knowledge Acquisition, Los Angeles, CA, July 1992 P 92-11 De Jong, K. A. and Sarma, J., "Generation Gaps Revisited," Proceedings of the Second Workshop on Foundations of Genetic Algorithms, Morgan Kaufmann, July 1992. P 92-12 De Jong, K. A., "Genetic Algorithms are NOT Function Optimizers," Proceedings of the Second Workshop on Foundations of Genetic Algorithms, Morgan Kaufmann, July 1992. P 92-13 Michalski, R. S., Kerschberg, L., Kaufman, K. and Ribeiro, J., "Mining For Knowledge in Databases: The INLEN Architecture, Initial Implementation and First Results," Intelligent Information Systems: Integrating Artificial Intelligence and Database Technologies, Vol. 1, No. 1, pp. 85-113, August ,1992. P 92-14 Kulpa, Z. and Sobolewski, M., "Knowledge-directed Graphical and Natural Language Interface with a Knowledge-based Concurrent Engineering Environment," Proceedings of the 8th International Conference on CAD/CAM, Robotics and Factories of the Future, Metz, France, August 1992. P 92-15 Pachowicz, P. W., Bala, J. W. and Zhang, J., "Methodology for Iterative Noise-Tolerant Learning and Its Application to Object Recognition in Computer Vision," Proceedings of the 6th International Conference on Systems Research, Informatics and Cybernetics, Baden-Baden, Germany, August 1992. P 92-16 Pachowicz, P. W., Hieb, M. R. and Mohta, P., "A Learning-Based Incremental Model Evolution for Invariant Object Recognition," Proceedings of the 6th International Conference on Systems Research, Informatics and Cybernetics, Baden-Baden, Germany, August 1992 P 92-17 Tecuci, G., "Automating Knowledge Acquisition as Extending, Updating and Improving a Knowledge Base," IEEE Transactions on Systems, Man, and Cybernetics, Vol. 22, No. 6, pp. 1444-1460, November/December 1992. P 92-18 Michalski, R. S., "Inferential Theory of Learning: Developing Foundations for Multistrategy Learning," Reports of the Machine Learning and Inference Laboratory, MLI 92-3, George Mason University, Fairfax, VA, September, 1992. P 92-19 Wnek, J. and Michalski, R. S., "Comparing Symbolic and Subsymbolic Learning: Three Studies," Reports of the Machine Learning and Inference Laboratory, MLI 92-4, George Mason University, Fairfax, VA, September, 1992. P 92-20 De Jong, K. A., "Are Genetic Algorithms Function Optimizers?," Proceedings of PPSN-92, the 2nd Conference on Parallel Problem Solving from Nature, Brussels, Belgium, Elsevier-Holland, September 1992. P 92-21 Gomaa, H., Kerschberg, L. and Sugumaran, V., "A Knowledge-Based Approach to Generating Target Systems Specifications from a Domain Model," Proceedings of IFIP World Computer Congress, Madrid, Spain, September 1992. P 92-22 Vamos, T., "Epistemology, Uncertainty and Social Change," Reports of the Machine Learning and Inference Laboratory, MLI 92-5, George Mason University, Fairfax, VA, October 1992. P 92-23 Pachowicz, P. W., "A Learning-Based Evolution of Concept Descriptions for an Adaptive Object Recognition," Proceedings of the 4th International Conference on Tools with Artificial Intelligence, Arlington, VA, pp. 316-323, November 1992. P 92-24 Pachowicz, P. W., Bala, J. W. and Zhang, J., "Iterative Rule Simplification for Noise Tolerant Inductive Learning," Proceedings of the 4th International Conference on Tools with Artificial Intelligence, Arlington, VA, pp. 452-453, November 1992. P 92-25 Vafaie, H. and De Jong, K. A., "Genetic Algorithms as a Tool for Feature Selection in Machine Learning," Proceedings of the 4th International Conference on Tools with Artificial Intelligence, Arlington, VA, November 1992. P 92-26 Seligman, L. and Kerschberg, L., "Approximate Knowledge Base/Database Consistency: An Active Database Approach," Proceedings of the First International Conference on Information and Knowledge Management, Baltimore, MD, November 1992. P 92-27 Yoon, J. P. and Kerschberg, L., "A Framework for Constraint Management in Object-Oriented Databases," Proceedings of the First International Conference on Information and Knowledge Management, Baltimore, MD, November 1992. P 92-28 Crain, S. and Hamburger, H., "Semantics, Knowledge and NP Modification," Formal Grammar: Theory and Implementation, R. Levine (Ed.), Oxford, England, Oxford University Press, 1992. P 92-29 Hamburger, H. and Hashim, R., "Foreign Language Tutoring and Learning Environment," Intelligent Tutoring Systems for Foreign Language Learning, M. Swartz and M. Yazdani (Eds.), New York & Berlin, Springer Verlag, 1992. P 92-30 Hamburger, H. and Lodgher, A., "Semantically Constrained Exploration and Heuristic Guidance," Intelligent Instruction by Computer, J. Psotka and M. Farr (Eds.), New York, Taylor and Francis, 1992. P 92-31 Hamburger, H. and Hashim, R., "Discourse Style and Situation Viewpoint for a Conversational Language Tutor," Proceedings of the International Conference on Computer- Assisted Learning, Wolfville, Nova Scotia, Canada, Springer-Verlag, New York, 1992. P 92-32 Pan, J. and Hamburger, H., "A Knowledge-based Learning System for Chinese Character Writing," Proceedings of the International Conference on Computer Processing of Chinese and Oriental Languages, Clearwater Beach, FL, December 15-19, 1992. P 92-33 Hieb, M. R. and Tecuci, G., "Two Methods for Consistency-driven Knowledge Elicitation," Reports of the Machine Learning and Inference Laboratory, MLI 92-6, George Mason University, Fairfax, VA, December 1992. P 92-34 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. P 92-35 Tecuci, G. and Hieb, M. R., "Consistency-driven Knowledge Elicitation: Using a Machine Learning Oriented Knowledge Representation to Integrate Learning and Knowledge Elicitation in NeoDISCIPLE," Reports of the Machine Learning and Inference Laboratory, MLI 92-8, George Mason University, Fairfax, VA, December 1992. P 92-36 Arciszewski, T., Dybala, T. and Wnek, J., "A Method for Evaluation of Learning Systems," HEURISTICS, The Journal of Knowledge Engineering, Special Issue on Knowledge Acquisition and Machine Learning, Vol. 5, No. 4, pp. 22-31, 1992. P 92-37 Hieb, M. R., Silverman, B. G. and Mezher, T. M., "Rule Acquisition for Dynamic Engineering Domains," HEURISTICS, The Journal of Knowledge Engineering, Special Issue on Knowledge Acquisition and Machine Learning, Vol. 5, No. 4, pp. 72-82, 1992. P 92-38 Wnek, J. and Michalski, R. S., "Experimental Comparison of Symbolic and Subsymbolic Learning," HEURISTICS, The Journal of Knowledge Engineering, Special Issue on Knowledge Acquisition and Machine Learning, Vol. 5, No. 4, pp. 1-21, 1992. P 92-39 Bala, J. W. and Pachowicz, P. W., "Recognizing Noisy Pattern Via Iterative Optimization and Matching of Their Rule Description," International Journal on Pattern Recognition and Artificial Intelligence, Vol. 6, No. 4, 1992. P 92-40 Michalski, R. S., "LEARNING = INFERENCING + MEMORIZING: Basic Concepts of Inferential Theory of Learning and Their Use for Classifying Learning Processes," Cognitive Models of Learning, 1992. P 92-41 Bala, J. W., Bloedorn, E., De Jong, K. A., Kaufman, K., Michalski, R. S., Pachowicz, P. W., Vafaie, H., Wnek, J. and Zhang, J., "A Brief Review of AQ Learning Programs and Their Application to the MONKS Problems," Reports of the Machine Learning and Inference Laboratory,MLI 92-9, George Mason University, Fairfax, VA, 1992. P 92-42 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. 1991 P 91-1 Michalski, R. S., "Searching for Knowledge in a World Flooded with Facts ," Applied Stochastic Models and Data Analysis, Vol 7, pp 153-166, 1991. P 91-2 Bala, J. W. and Pachowicz, P. W., "Application of Symbolic Machine Learning to the Recognition of Texture Concepts," Proceedings of the 7th IEEE Conference on Artificial Intelligence Application, Miami, FL, 1991. P 91-3 Pachowicz, P. W. and Bala, J. W., "Optimization of Concept Prototypes for the Recognition of Noisy Texture Data," Reports of the Machine Learning and Inference Laboratory, MLI 91-1, School of Information Technology and Engineering, George Mason University, Fairfax, VA, , 1991. P 91-4 Pachowicz, P. W., "Learning Invariant Texture Characteristics to Dynamic Environments A Model Evolution," Reports of the Machine Learning and Inference Laboratory, MLI 91-2, School of Information Technology and Engineering, George Mason University, Fairfax, VA, 1991. P 91-5 Tecuci, G., "A Multistrategy Learning Approach to Domain Modeling and Knowledge Acquisition," Proceedings of the European Conference on Machine Learning, Y. Kodratoff (Ed.), Porto, Portugal, Springer-Verlag, 1991. P 91-6 Tecuci, G. and Michalski, R. S., "Input Understanding as a Basis for Multistrategy Task-adaptive Learning in Ras Zand Zemankova M eds," Proceedings of the International Symposium on Methodologies for Intelligent Systems, Lecture Notes on Artificial Intelligence, Springer-Verlag, 1991. P 91-7 Michalski, R. S., "Searching for Knowledge in a World Flooded with Facts," an invited talk, Proceedings of the Fifth International Symposium on Applied Stochastic Models and Data Analysis, Granada, Spain, April 23-26 ,1991. P 91-8 Kerschberg, L. and Weishar, D., "An Intelligent Heterogeneous Autonomous Database Architecture for Semantic Heterogeneity Support," IEEE Workshop on Interoperability in Multidatabase Systems, Kyoto, Japan, April 1991. P 91-9 Bergadano, F., Matwin, S., Michalski, R. S. and Zhang, J., "Learning Two-tiered Descriptions of Flexible Concepts The POSEIDON System," Reports of the Machine Learning and Inference Laboratory, MLI 91-3, School of Information Technology and Engineering, George Mason University, Fairfax, VA,, May, 1991 . P 91-10 Wnek, J. and Michalski, R. S., "Hypothesis-Driven Constructive Induction in AQ17 A Method and Experiments," Reports of the Machine Learning and Inference Laboratory, MLI 91-4, School of Information Technology and Engineering, George Mason University, Fairfax, VA, May, 1991. P 91-11 Tecuci, G. and Michalski, R. S., "A Method for Multistrategy Task-adaptive Learning Based on Plausible Justifications," Machine Learning: Proceedings of the Eighth International Workshop, San Mateo, CA, , Morgan Kaufmann, June, 1991. P 91-12 Pachowicz, P. W. and Bala, J. W., "Optimization of Concept Prototypes for the Recognition of Noisy Texture Data," Machine Learning Proceedings of the Eighth International Workshop, San Mateo, CA,, Morgan Kaufmann, June 1991. P 91-13 Michalski, R. S., "Toward a Unified Theory of Learning: An Outline of Basic Ideas," Invited paper, First World Conference on the Fundamentals of Artificial Intelligence, Paris, France, July 1-5, 1991. P 91-14 Pachowicz, P. W. and Bala, J. W., "Texture Recognition Through Machine Learning and Concept Optimization," Reports of the Machine Learning and Inference Laboratory, MLI 91-5, School of Information Technology and Engineering, George Mason University, Fairfax, VA, July 1991. P 91-15 Tecuci, G., "Steps Toward Automating Knowledge Acquisition for Expert Systems," Proceedings of the AAAI-91 Workshop on Knowledge Acquisition "From Science To Technology to Tools," , Anaheim, CA, July 1991. P 91-16 Kaufman, K., Michalski, R. S. and Kerschberg, L., "An Architecture for Integrating Machine Learning and Discovery Programs into a Data Analysis System," Proceedings of the AAAI-91 Workshop on Knowledge Discovery in Databases, Anaheim,CA, July, 1991. P 91-17 Spears, W. and De Jong, K. A., "An Analysis of Multi-point Crossover," Foundations of Genetic Algorithms, San Mateo, Morgan Kaufmann, July 1991. P 91-18 Spears, W. and De Jong, K. A., "On the Virtues of Parameterized Uniform Crossover," Proceedings of the 4th International Conference on Genetic Algorithms, Morgan Kaufmann, July, 1991. P 91-19 Wnek, J. and Michalski, R. S., "Hypothesis-Driven Constructive Induction in AQ17: A Method and Experiments ," Proceedings of the IJCAI-91 Workshop on Evaluating and Changing Representation in Machine Learning, Sydney, Australia, August, 1991. P 91-20 De Jong, K. A. and Spears, W., "Learning Concept Classification Rules Using Genetic Algorithms," Proceedings of IJCAI-91, Sydney, Australia, Morgan Kaufmann, August 1991. P 91-21 Kerschberg, L. and Seligman, L., "Federated Knowledge and Database Systems: A New Architecture for Integrating of AI and Database Systems," Proceedings of the IJCAI-91 Workshop on Integrating Artificial Intelligence and Databases, Sydney, Australia, August 1991. P 91-22 Michalski, R. S., "Beyond Prototypes and Frames: The Two-tiered Concept Representation," Reports of the Machine Learning and Inference Laboratory, MLI 91-6, School of Information Technology and Engineering, George Mason University, September, 1991. P 91-23 Tecuci, G., "Automating Knowledge Acquisition As Extending, Updating, and Improving A Knowledge Base," Reports of the Machine Learning and Inference Laboratory, MLI 91-7, School of Information Technology and Engineering, George Mason University, Fairfax, VA, September 1991. P 91-24 Michael, J. B., "Validation, Verification, and Experimentation with Abacus2," Reports of the Machine Learning and Inference Laboratory, MLI 91-8, School of Information Technology and Engineering, George Mason University, Fairfax, VA, September 1991. P 91-25 De Jong, K. A., Pachowicz, P. W. and Bala, J. W., "Using Genetic Algorithms to Improve the Performance of Classification Rules Produced by Symbolic Inductive Method," Proceedings of the Sixth International Symposium on Methodologies for Intelligent Systems, ISMIS'91, Charlotte, North Carolina, October 16-19, 1991. P 91-26 Kaufman, K., Michalski, R. S. and Kerschberg, L., "Knowledge Extraction from Databases: Design Principles of the INLEN System," Proceedings of the Sixth International Symposium on Methodologies for Intelligent Systems, ISMIS '91, October 16-19, 1991. P 91-27 Michalski, R. S., "Inferential Learning Theory: A Conceptual Framework for Characterizing Learning Processes," Reports of the Machine Learning and Inference Laboratory, MLI 91-9, School of Information Technology and Engineering, George Mason University, Fairfax, VA, October, 1991. P 91-28 Thrun, S. B., Bala, J. W., Bloedorn, E., Bratko, I., Cestnik, B., Cheng, J., De Jong, K. A., Dzeroski, S., Fahlman, S. E., Hamann, R., Kaufman, K., Keller, S., Kononenko, I., Kreuziger, J., Michalski, R. S., Mitchell, T. M., Pachowicz, P., Vafaie, H., Van de Velde, W., Wenzel, W., Wnek, J. and Zhang, J., "The MONK's problems: A Performance Comparison of Different Learning Algorithms," , Carnegie Mellon University, Pittsburgh, PA, October, 1991. P 91-29 Kerschberg, L. and Baum, R., "A Taxonomy of Knowledge-Based Approaches to Fault Management for Telecommunications Networks," IEEE Conference on Systems, Man and Cybernetics, Charlottesville, VA, October 1991. P 91-30 Pachowicz, P., "Recognizing and Incrementally Evolving Texture Concepts in Dynamic Environments: An Incremental Model Generalization Approach," Reports of the Machine Learning and Inference Laboratory, MLI 91-10, School of Information Technology and Engineering, George Mason, University, Fairfax, VA, November 1991. P 91-31 Michalski, R. S. and Tecuci, G. (Eds.), Proceedings of the 1st International Workshop on Multistrategy Learning, MSL-91, Harpers Ferry, WV, 1991. P 91-32 Michalski, R. S., "Inferential Learning Theory as a Basis for Multistrategy Task-Adaptive Learning ," Proceedings of the First International Workshop on Multistrategy Learning, MSL-91, Harpers Ferry, WV, 3-18, 1991. P 91-33 Wnek, J. and Michalski, R. S., "An Experimental Comparison of Symbolic and Subsymbolic Learning Paradigms: Phase I -- Learning Logic-Style Concepts," Proceedings of the First International Workshop on Multistrategy Learning, MSL-91, Harpers Ferry, WV, November 7-9, 1991. P 91-34 Vafaie, H. and De Jong, K. A., "Improving the Performance of a Rule Induction System Using Genetic Algorithm," Proceedings of the First International Workshop on Multistrategy Learning, MSL-91, Harpers Ferry, WV, November 7-9, 1991. P 91-35 Bala, J. W., De Jong, K. A. and Pachowicz, P., "Integration of Inductive Learning and Genetic Algorithms to Learn Optimal Concept Descriptions from Engineering Data," Proceedings of the First International Workshop on Multistrategy Learning, MSL-91, Harpers Ferry, WV, November 7-9, 1991. P 91-36 Tecuci, G., "Learning as Understanding the External World," Proceedings of the First International Workshop on Multistrategy Learning, MSL-91, Harpers Ferry, WV, November 7-9, 1991. P 91-37 Bloedorn, E. and Michalski, R. S., "Data Driven Constructive Induction in AQ17-PRE: A Method and Experiments," Proceedings of the Third International Conference on Tools for AI, San Jose, CA, November 9-14, 1991. P 91-38 Bala, J. W. and Michalski, R. S., "Learning Textural Concepts Through Multilevel Symbolic Transformations," Proceedings of the Third International Conference on Tools for Artificial Intelligence, San Jose, CA, November 9-14, 1991. P 91-39 Janssen, T., Bloedorn, E., Hieb, M. R. and Michalski, R. S., "Learning Rules for Preventing and Diagnosing Faults in Large-Scale Data Communications Networks: An Exploratory Study," Proceedings of the Fourth International Symposium on Artificial Intelligence, Cancun, Mexico, November 13-15. 1991. P 91-40 Pachowicz, P., "Application of Symbolic Inductive Learning to the Acquisitions and Recognition of Noisy Texture Concepts," Applications of Learning and Planning Methods, November 1991. P 91-41 Gomaa, H., Kerschberg, L., Bosch, C., Sugumaran, V. and Tavakoli, I., "A Prototype Software Engineering Environment for Domain Modeling and Reuse," NASA/Goddard Sixteenth Annual Software Engineering Workshop, December 4-5, 1991. P 91-42 Weishar, D. and Kerschberg, L., "Data/Knowledge Packets as a Means of Supporting Semantic Heterogeneity in Multidatabase Systems," ACM SIGMOD Record, December 1991. P 91-43 Kaufman, K., Michalski, R. S. and Kerschberg, L., "Mining for Knowledge in Databases: Goals and G