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Extending Explanation-Based Learning by Generalizing the Structure of Explanations

Extending Explanation-Based Learning by Generalizing the Structure of Explanations presents several fully-implemented computer systems that reflect theories of how to extend an interesting subfield of machine learning called explanation-based learning. This book discusses the need for generalizing explanation structures, relevance to research areas outside machine learning, and schema-based problem solving. The result of standard explanation-based learning, BAGGER generalization algorithm, and empirical analysis of explanation-based learning are also elaborated. This text likewise covers the effect of increased problem complexity, rule access strategies, empirical study of BAGGER2, and related work in similarity-based learning. This publication is suitable for readers interested in machine learning, especially explanation-based learning.

Learning. in. Mathematically-Based. Domains. All the mathematical sciences are
founded on relations between physical laws and laws of numbers, so that the aim
of exact science is to reduce the problems of nature to the determination of
quantities by operations with numbers. James Clerk Maxwell ...