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Case-Based Knowledge and Planning

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  • Itzhak Gilboa
  • David Schmeidler

Abstract

"Case-Based Decision Theory" is a theory of decision making under uncertainty, suggesting that people tend to choose acts that performed well in similar cases they recall. The theory has been developed from a decision-/game-/economic-theoretical point of view, as a potential alternative to expected utility theory. In this paper we attempt to re-consider CBDT as a theory of knowledge representation and of planning, to contrast it with the rule-based approach, and to study its implications regarding the process of induction.

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Bibliographic Info

Paper provided by Northwestern University, Center for Mathematical Studies in Economics and Management Science in its series Discussion Papers with number 1127.

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Date of creation: Apr 1995
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Handle: RePEc:nwu:cmsems:1127

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  1. Gilboa, Itzhak & Schmeidler, David, 1996. "Case-Based Optimization," Games and Economic Behavior, Elsevier, vol. 15(1), pages 1-26, July.
  2. Itzhak Gilboa & David Schmeidler, 1996. "Act similarity in case-based decision theory (*)," Economic Theory, Springer, vol. 9(1), pages 47-62.
  3. Itzhak Gilboa, 1990. "Philosophical Applications of Kolmogorov's Complexity Measure," Discussion Papers 923, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
  4. Schmeidler, David, 1989. "Subjective Probability and Expected Utility without Additivity," Econometrica, Econometric Society, vol. 57(3), pages 571-87, May.
  5. Itzhak Gilboa & David Schmeidler, 1992. "Case-Based Decision Theory," Discussion Papers 994, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
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Cited by:
  1. Akihiko Matsui & In-Koo Cho, 2010. "Aspiration, Sympathy and Minmax Outcome," 2010 Meeting Papers 57, Society for Economic Dynamics.

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