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Issue No.02 - April (1990 vol.5)
pp: 15-28
ABSTRACT
<p>Research in equipping rule-based expert systems with skill refinement behavior by utilizing the recognize-act control mechanism is described. An overview of expert system skill refinement is provided. A skill refinement model for generating plans is then presented. Two closely coupled and mutually supportive mechanisms characterize this model: a rule-selecting mechanism (corresponding to a buyer-selecting procedure) that dynamically incorporates the concept of multiple selection/preference criteria into the conflict resolution process, and an economics-based credit assignment mechanism (corresponding to a capital reallocation procedure) that uses an inference engine's experiences to update the potentiality of each rule participating in the problem-solving process. A mathematical description of the model is given. An example is provided to illustrate the inference engine's skill refinement and the applicability of the model is discussed.</p>
CITATION
Pi-Sheng Deng, Clyde W. Holsapple, Andrew B. Whinston, "A Skill Refinement Learning Model for Rule-Based Expert Systems", IEEE Intelligent Systems, vol.5, no. 2, pp. 15-28, April 1990, doi:10.1109/64.53179
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