Explanation-Based Learning
Most machine learning is focused on inductive generalization from empirical data and does not explicitly exploit prior knowledge of the domain. Explanation-based learning is a radically different approach that uses existing declarative domain knowledge to "explain" individual examples and uses this explanation to drive a knowledge-based generalization of the example. It is therefore capable of learning a very general concept from only a single training example. Our work was some of the original research on this approach and lead to our subsequent work on theory refinement and on learning for planning and problem-solving.
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Bayesian Logic Programs for Plan Recognition and Machine Reading 2012
Sindhu Raghavan, PhD Thesis, Department of Computer Science, University of Texas at Austin. 170.
Integrating EBL and ILP to Acquire Control Rules for Planning 1996
Tara A. Estlin and Raymond J. Mooney, Proceedings of the Third International Workshop on Multi-Strategy Learning (MSL-96) (1996), pp. 271--279.
Integrating ILP and EBL 1994
Raymond J. Mooney and John M. Zelle, Sigart Bulletin (special issue on Inductive Logic Programmming), Vol. 5, 1 (1994), pp. 12-21.
Combining FOIL and EBG to Speed-Up Logic Programs 1993
John M. Zelle and Raymond J. Mooney, In Proceedings of the 13th International Joint Conference on Artificial Intelligence, pp. 1106-1111 1993. San Francisco, CA: Morgan Kaufmann.
Induction Over the Unexplained: Using Overly-General Domain Theories to Aid Concept Learning 1993
Raymond J. Mooney, Machine Learning, Vol. 10 (1993), pp. 79-110.
Integrating Theory and Data in Category Learning 1993
Raymond J. Mooney, In Categorization by Humans and Machines, G. V. Nakamura and D. L. Medin and R. Taraban (Eds.), pp. 189-218 1993.
Schema acquisition from a single example 1992
W. Ahn, W. F. Brewer and Raymond J. Mooney, Journal of Experimental Psychology: Learning, Memory, and Cognition, Vol. 18 (1992), pp. 391-412.
Speeding-up Logic Programs by Combining EBG and FOIL 1992
John M. Zelle and Raymond J. Mooney, In Proceedings of the 1992 Machine Learning Workshop on Knowledge Compilation and Speedup Learning, Aberdeen, Scotland, July 1992.
Learning Plan Schemata From Observation: Explanation-Based Learning for Plan Recognition 1990
Raymond J. Mooney, Cognitive Science, Vol. 14, 4 (1990), pp. 483-509.
Controlling Search for the Consequences of New Information during Knowledge Integration 1989
K. Murray and Bruce Porter , In Proceedings of the Sixth International Workshop on Machine Learning, pp. 290-295, Ithaca, NY, June 1989.
The Effect of Rule Use on the Utility of Explanation-Based Learning 1989
Raymond J. Mooney, In Proceedings of the 11th International Joint Conference on Artificial Intelligence, pp. 725-730 1989. San Francisco, CA: Morgan Kaufmann.
A General Explanation-Based Learning Mechanism and its Application to Narrative Understanding 1988
Raymond J. Mooney, Ph.D. thesis, Department of Computer Science, University of Illinois at Urbana-Champaign, 1988
Generalizing the Order of Operators in Macro-Operators 1988
Raymond J. Mooney, In Proceedings of the Fifth International Conference on Machine Learning (ICML-88), pp. 270-283, Ann Arbor, MI, June 1988.
Integrated Learning of Words and their Underlying Concepts 1987
Raymond J. Mooney, In Proceedings of the Ninth Annual Conference of the Cognitive Science Society, pp. 947-978, Seattle, WA, July 1987.
Schema Acquisition from One Example: Psychological Evidence for Explanation-Based Learning 1987
W. Ahn, Raymond J. Mooney, W.F. Brewer and G.F. DeJong, In Proceedings of the Ninth Annual Conference of the Cognitive Science Society, pp. 50-57, Seattle, WA, July 1987.
A Domain Independent Explanation-Based Generalizer 1986
Raymond J. Mooney and S.W. Bennett, In Proceedings of the Fifth National Conference on Artificial Intelligence (AAAI-86), pp. 551-555, Philadelphia, PA, August 1986.
Explanation-Based Learning: An Alternative View 1986
G.F. DeJong and Raymond J. Mooney, Machine Learning (1986), pp. 145-176.
Generalizing Explanations of Narratives into Schemata 1985
Raymond J. Mooney, Masters Thesis, Department of Computer Science, University of Illinois at Urbana-Champaign.
Learning Schemata for Natural Language Processing 1985
Raymond J. Mooney and Gerald F. DeJong, In Proceedings of the Ninth International Joint Conference on Artificial Intelligence (IJCAI-85), pp. 681-687, Los Angeles, CA, August 1985.