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软件学报  1995 

THE PRINCIPLES AND IMPLEMENTATION OF ANALOGICAL TRANSFER
类比转换原理及其实现

Keywords: Analogical transfer,analogical reasoning,machine learning,analogical learning
类比转换,类比推理,机器学习,类比学习

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Abstract:

Analogical transfer process carries knowledge from a known situation(the base) over to a similar new situation(the target) so that one can solve the target or obtain new knowledge about the target.The principles of analogical transfer in this paper discuss how to select the best mapping,how to create objects and predicates in the target, and which proposition of the base to be transferred into the target. On the basis of the principles, the paper designs a computational model of analogical transfer and implements an analogical transfer engine called ATE.The case study illustrates analogical conclusions produced by ATE are with both creativity and higher certainty degree.

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