Learning by Analogy: Formulating and Generalizing Plans from Past Experience
作者： Jaime G. Carbonell
DOI: 10.1007/978-3-662-12405-5_5
关键词:
摘要: Analogical reasoning is a powerful mechanism for exploiting past experience in planning and problem solving. This chapter outlines theory of analogical solving based on an extension to means-ends analysis. An transformation process developed extract knowledge from successful problem-solving situations that bear strong similarity the current problem. Then, investigation focuses extending model generate useful exemplary solutions related problems which more general plans can be induced refined. Starting with inference engine, is, essence, compiled incrementally into effective procedures solve various classes increasingly reliable direct manner.
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