Abstract
We present a similarity criterion based on feature weighting. Feature weights are recomputed dynamically according to the performance of cases during planning episodes. We will also present a novel algorithm to analyze and explain the performance of the retrieved cases and to determine the features whose weights need to be recomputed. Experiments show that the integration of our similarity criterion in a feature weighting model and our analysis algorithm improves the adaptability of the retrieved cases over a period of multiple problem solving episodes.
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References
Aamodt, A., & Plaza, E. (1994). Case-based reasoning: Foundation issues, methodological variations and system approaches. AI-Communications, 7(1), pp 39–59.
Barrett, A., & Weld, D. (1994). Partial-order planning: Evaluating possible efficiency gains. Artificial Intelligence, 67(1), 71–112.
Fox, S., & Leake, D. (1995). Using introspective reasoning to refine indexing. In (Veloso & Aamodt, 1995).
Ihrig, L., & Kambhampati, S. (1994). Derivational replay for partial-order planning. In Proceedings of AAAI-94, pp. 116–125.
Ihrig, L., & Kambhampati, S. (1995). Automatic storage and indexing of plan derivations based on replay failures. In Proceedings of IJCAI-95.
Kambhampati, S., Katukam, S., & Qu, Y. (1995). Failure driven dynamic search control for partial order planners: An explanation-based approach. Artificial Intelligence. (submitted, ASU-CSE-TR-95-010).
Leake, D. B., Kinley, A., & Wilson, D. (1995). Learning to improve case adaptation by introspective reasoning and cbr. In (Veloso & Aamodt, 1995).
McAllester, D., & Rosenblitt, D. (1991). Systematic nonlinear planning. In Proceedings of AAAI-91, pp. 634–639.
Minton, S. (1988). Learning Search Control Knowledge: An Explanation-Based Approach. Kluwer Academic Publishers, Boston.
Muñoz-Avila, H., & Hüllen, J. (1995). Retrieving relevant cases by using goal dependencies. In (Veloso & Aamodt, 1995).
Muñoz-Avila, H., Paulokat, J., & Wess, S. (1995). Controlling non-linear hierarchical planning by case replay. In Keane, M., Halton, J., & Manago, M. (Eds.), Advances in Case-Based Reasoning. Selected Papers of the 2nd European Workshop (EWCBR-94), No. 984 in Lecture Notes in Artificial Intelligence. Springer.
Muñoz-Avila, H., & Weberskirch, F. (1996). Planning for manufacturing workpieces by storing, indexing and replaying planning decisions. In Third International Conference on AI Planning Systems (AIPS-96). AAAI-Press.
Paulokat, J., & Wess, S. (1994). Planning for machining workpieces with a partial-order nonlinear planner. In Gil, Y., & Veloso, M. (Eds.), AAAI-Working Notes’ Planning and Learning: On To Real Applications' New Orleans.
Richter, M., Wess, S., Althoff, K., & Maurer, F. (Eds.). (1994). First European Workshop on Case-base Reasoning (EWCBR-93). No. 837 in Lecture Notes in Artificial Intelligence. Springer Verlag.
Salzberg, S. L. (1991). A nearest hyperrectangle learning method. Machine Learning, 1.
Smyth, B., & Keane, M. (1994). Retrieving adaptable cases. In Richter, M., Wess, S., Althoff, K.-D., & Maurer, F. (Eds.), Proceedings of the 1st European Workshop on Case-Based Reasoning (EWCBR-93), No. 837 in LNAI. Springer.
Smyth, B., & Keane, M. (1995). Experiments on adaptation-guided retrieval in case-based design. In (Veloso & Aamodt, 1995).
Veloso, M. (1992). Learning by Analogical Reasoning in General Problem Solving. Ph.D. thesis, Carnegie Mellon University.
Veloso, M. (1994a). Planning and learning by analogical reasoning. No. 886 in Lecture Notes in Artificial Intelligence. Springer Verlag.
Veloso, M. (1994). Prodigy/analogy: Analogical reasoning in general problem solving. In (Richter, Wess, Althoff, & Maurer, 1994).
Veloso, M., & Aamodt, A. (Eds.). (1995). Case-Based Reasoning Research and Development, Proceedings of the 1st International Conference (ICCBR-95). No. 1010 in Lecture Notes in Artificial Intelligence. Springer Verlag.
Weberskirch, F. (1995). Combining SNLP-like planning and dependencymaintenance. Tech. rep. LSA-95-10E, Centre for Learning Systems and Applications, University of Kaiserslautern, Germany.
Wettschereck, D., & Aha, D. W. (1995). Weighting features. In (Veloso & Aamodt, 1995).
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Muñoz-Avila, H., Hüllen, J. (1996). Feature weighting by explaining case-based planning episodes. In: Smith, I., Faltings, B. (eds) Advances in Case-Based Reasoning. EWCBR 1996. Lecture Notes in Computer Science, vol 1168. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020617
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DOI: https://doi.org/10.1007/BFb0020617
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