Extending Explanation-Based Learning by Generalizing the Structure of Explanations - Info and Reading Options
By Jude W. Shavlik
"Extending Explanation-Based Learning by Generalizing the Structure of Explanations" was published by Elsevier Science & Technology Books in 2014 - Erscheinungsort nicht ermittelbar, it has 1 pages and the language of the book is English.
“Extending Explanation-Based Learning by Generalizing the Structure of Explanations” Metadata:
- Title: ➤ Extending Explanation-Based Learning by Generalizing the Structure of Explanations
- Author: Jude W. Shavlik
- Language: English
- Number of Pages: 1
- Publisher: ➤ Elsevier Science & Technology Books
- Publish Date: 2014
- Publish Location: ➤ Erscheinungsort nicht ermittelbar
“Extending Explanation-Based Learning by Generalizing the Structure of Explanations” Subjects and Themes:
- Subjects: ➤ Artificial intelligence - Comprehension (Theory of knowledge) - Explanation-based learning
Edition Specifications:
- Pagination: 236
Edition Identifiers:
- The Open Library ID: OL40423976M - OL4790791W
- ISBN-13: 9781483258911
- All ISBNs: 9781483258911
AI-generated Review of “Extending Explanation-Based Learning by Generalizing the Structure of Explanations”:
"Extending Explanation-Based Learning by Generalizing the Structure of Explanations" Description:
Open Data:
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
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