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Logic for Learning Learning Comprehensible Theories from Structured Data at Meripustak

Logic for Learning Learning Comprehensible Theories from Structured Data by John W. Lloyd , Springer

Books from same Author: John W. Lloyd

Books from same Publisher: Springer

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  • General Information  
    Author(s)John W. Lloyd
    PublisherSpringer
    ISBN9783642075537
    Pages257
    BindingPaperback
    LanguageEnglish
    Publish YearOctober 2010

    Description

    Springer Logic for Learning Learning Comprehensible Theories from Structured Data by John W. Lloyd

    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._x000D_ Table of contents :- _x000D_ 1. Introduction.- 2. Logic.- 3. Individuals.- 4. Predicates.- 5. Computation.- 6. Learning.- A. Appendix.- A.1 Well-Founded Sets.- References.- Notation._x000D_



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