Logic for learning : learning comprehensible theories from structured data
著者
書誌事項
Logic for learning : learning comprehensible theories from structured data
（Cognitive technologies）
Springer, c2010
- : pbk.
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注記
Includes bibliographical references (p. [245]-249) and index
内容説明・目次
内容説明
This book provides a systematic approach to knowledge representation, computation, and learning using higher-order logic. For those interested in computational logic, it provides a framework for knowledge representation and computation based on higher-order logic, and demonstrates its advantages over more standard approaches based on first-order logic. For those interested in machine learning, the book explains how higher-order logic provides suitable knowledge representation formalisms and hypothesis languages for machine learning applications.
目次
1. Introduction.- 2. Logic.- 3. Individuals.- 4. Predicates.- 5. Computation.- 6. Learning.- A. Appendix.- A.1 Well-Founded Sets.- References.- Notation.
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