Abstract
In this paper, we propose the CCAR (Combining Case-based And Rule-based reasoning) model for an exception handling of Rule-based Reasoning using Case-based Reasoning. The central idea of the model proposed in this paper is to represent the exception of a rule as a case, and to utilize the case for a solution to a problem, and then to search the case memory to retrieve a case which violates the conclusion of a rule. If the similarity between a target problem and the selected case is high, the conclusion of a case is applied. Otherwise, the conclusion of rule-based reasoning is applied.
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References
Allen, J. A. and Langley, P.: A unified framework for planning and learning, in: Proc. of Workshop on Innovative Approaches to Planning, Scheduling, and Control, San Diego, 1990.
Barletta, R. and Mark, W.: Explanation-based indexing of cases, in: Proc. of the CBRWorkshop, 1988.
Branting, L. K.: Building explanations from rules and structured cases, Internat. J. Man– Machine Studies (1991).
Dutta, S. and Bonissone, P. P.: Integrating case-based and rule-based reasoning: The possibilistic connection, in: Proc. of the 6th Conf. on Uncertainty in Artificial Intelligence, July 1990.
Goel, A. and Chandrasekaran, B.: Integrating model-based reasoning and case-based reasoning, in: Proc. of the AAAI Workshop on AI in Design, American Association for Artificial Intelligence, 1988.
Golding, A. R.: Pronouncing names by a combination of case-based and rule-based reasoning, PhD Thesis, Stanford University, 1991.
Fox, S. and Leake, D. B.: Combining case-based planning and introspective reasoning, in: Proc. of the 6th Midwest Artificial Intelligence and Cognitive Science Society Conference, II, 1993, pp. 32–36.
Kolodner, J.: Case-Based Reasoning, Morgan Kaufman, Los Altos, CA, 1993.
Koton, P.: Reasoning about evidence in causal explanations, in:Proc. of AAAI-88, 1988.
Leake, D. B.: Combining rules an cases to learn case adaptation, in: Proc. of the 17th Annual Conf. of the Cognitive Science Society, 1995.
Nakatani, Y. and Israel, D.: Tuning rules by cases, in: First European EWCBR-93, 1993, pp. 313–324.
Ram, A. and Santamaria, J. C.: A multistrategy case-based and reinforcement learning – approach to self-improving reactive control systems for autonomous robotic navigation, in: Proc. of the 2nd Internat. Workshop on Multistrategy Learning, Harpers Ferry, 1993.
Riesbeck, C. K. and Schank, R. C.: Inside Case-Based Reasoning, Lawrence Erlbaum Associates, New York, 1989.
Rissland, E. L. and Skalak, D. B.: Combining case-based reasoning and rule-based reasoning: A heuristic approach, in: Proc. of IJCAI-89, Detroit, 1989.
Skalak, D. B.: Options for controlling mixed paradigm systems, in: Proc. of Workshop on Case-Based Reasoning, 1989, p. 5.
Yao, B. and He, Y.: A hybrid system for case-based reasoning, in: World Congress on Neural Networks, Vol. 4, San Diego, 1993, pp. 442–446.
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Lee, M.R. An Exception Handling of Rule-Based Reasoning Using Case-Based Reasoning. Journal of Intelligent and Robotic Systems 35, 327–338 (2002). https://doi.org/10.1023/A:1021161418286
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DOI: https://doi.org/10.1023/A:1021161418286