Extending Explanation-Based Learning by Generalizing the Structure of Explanations
Author | : Jude W. Shavlik |
Publisher | : Morgan Kaufmann |
Total Pages | : 232 |
Release | : 2014-07-10 |
ISBN-10 | : 9781483258911 |
ISBN-13 | : 1483258912 |
Rating | : 4/5 (11 Downloads) |
Book excerpt: 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.