Abstract
Presenting multiple examples to an Explanation Based Learning system may lead to a lot of quite similar rules. This has a negative effect on the overall problem solving performance. The problem can be alleviated by combining several rules into one. We present a method to generalize rules by locating common parts and differences in order to obtain a more useful set of rules.
Supported by the Belgian National Fund for Scientific Research.
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Braverman, M.S., Russell, S.J., Boundaries of Operationality, Proceedings of the fifth International Conference on Machine Learning, Ann Arbor, MI, Morgan Kaufmann, 1988, pp. 221–234.
Cohen, W.W., Generalizing Number and Learning from Multiple Examples in Explanation Based Learning, Proceedings of the fifth International Conference on Machine Learning, Ann Arbor, MI, Morgan Kaufmann, 1988, pp. 256–269.
De Jong, G.F. and Mooney, R.J., Explanation Based Learning: An Alternative View. Machine Learning 1, 2 (April 1986), pp. 145–176.
De Jong, G., Some thoughts on the Present and Future of Explanation-Based Learning, Proceedings of the 8th ECAI, Pitman, London, 1988, pp. 690–697.
Genesereth, M.R., Nilsson, N.J., Logical Foundations of Artificial Intelligence. Morgan Kaufmann, Los Altos, 1987.
Hirsch, H., Explanation Based Generalization in a Logic-Programming Environment. IJCAI 87. Proceedings of the tenth International Joint Conference on Artificial Intelligence, 1987, pp. 221–227.
Kedar-Cabelli, S.T., Analogy with purpose in legal reasoning from precedents, (Technical Report LRP-TR-17), Laboratory for Computer Science Research, Rutgers University, New Brunswick, NJ, 1984.
Kedar-Cabelli, S.T., Purpose-directed analogy, Proceedings of the Cognitive Science Society Conference, Irvine, CA: Morgan Kaufmann, 1985.
Keller, M., Defining Operationality for Explanation-Based Learning, Proceedings of the Sixth National Conference on Artificial Intelligence, 1987, pp. 482–487.
Kowalski, R., Logic for problem solving, North Holland, New York, 1979.
Markovitch, S., Scott, P.D., The Role of Forgetting in Learning, Proceedings of the fifth International Conference on Machine Learning, Ann Arbor, MI, Morgan Kaufmann, 1988, pp. 459–465.
Minton, S., Carbonell, J.G., Strategies for Learning Search Control Rules: An Explanation Based Approach, IJCAI 87. Proceedings of the tenth International Joint Conference on Artificial Intelligence, 1987, pp. 228–235.
Minton, S., Quantitative Results Concerning the Utility of Explanation-Based Learning. Proceedings of AAAI 88, 1988, pp. 564–569.
Michalski, R.S., Learning From Observation: Conceptual Clustering, Machine Learning, an Artificial Intelligence Approach, Springer-Verlag, 1983, pp. 331–364.
Mitchell, T.M., Keller, R. and Kedar-Cabelli, S., Explanation Based Generalization. A Unifying View. Machine Learning 1, 1 (January 1986), pp. 47–80.
Sablon, G., Automatisch leren op basis van verklaringen voor trainingsvoorbeelden, Licentiate's thesis, Dept. of Computer Science K.U.Leuven, june 1988 (in Dutch).
Segre, A.M., On the operationality/generality trade-off in explanation-based learning. IJCAI 87. Proceedings of the tenth International Joint Conference on Artificial Intelligence, 1987, pp. 242–248.
Shavlik, J., De Jong, G., BAGGER: an EBL system that extends and generalizes explanations. Proceedings of the Sixth National Conference on Artificial Intelligence, 1987, pp. 516–520.
Shavlik, J., De Jong, G., An explanation-based approach to generalizing number. IJCAI 87. Proceedings of the tenth International Joint Conference on Artificial Intelligence, 1987, pp. 236–238.
Tambe, M., Newell, A., Some Chunks Are Expensive Proceedings of the fifth International Conference on Machine Learning, Ann Arbor, MI, Morgan Kaufmann, 1988, pp. 451–458.
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Sablon, G., De Raedt, L., Bruynooghe, M. (1989). Generalizing multiple examples in explanation based learning. In: Jantke, K.P. (eds) Analogical and Inductive Inference. AII 1989. Lecture Notes in Computer Science, vol 397. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-51734-0_60
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DOI: https://doi.org/10.1007/3-540-51734-0_60
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