Learning New Spatially-Oriented Game-Playing Agents through Experience

نویسندگان

  • Susan L. Epstein
  • Jack Gelfand
چکیده

As they gain expertise in problem solving, people increasingly rely on patterns and spatially-oriented reasoning. This paper describes the integration of an associative visual pattern classifier and the automated acquisition of new, spatially-oriented reasoning agents that simulate such behavior. They are incorporated into a game-learning program whose architecture robustly combines agents with conflicting perspectives. When tested on three games, the visual pattern classifier learns meaningful patterns, and the pattern-based, spatially-oriented agents generalized from these patterns are generally correct. The trustworthiness and relevance of these agents are confirmed with an algorithm that measures the accuracy of the contribution of each agent to the decision-mak-

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تاریخ انتشار 1995