Logic for Learning

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.

Contenu

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