Systems That Learn

An Introduction to Learning Theory

Formal learning theory is one of several mathematical approaches to the study of intelligent adaptation to the environment. The analysis developed in this book is based on a number theoretical approach to learning and uses the tools of recursive-function theory to understand how learners come to an accurate view of reality. This revised and expanded edition of a successful text provides a comprehensive, self-contained introduction to the concepts and techniques of the theory. Exercises throughout the text provide experience in the use of computational arguments to prove facts about learning.

Table of Contents

  1. Series Forward
  2. Preface
  3. 1. Introduction
  4. 2. Formalities
  5. 3. Identification
  6. 4. Identification by Computable Scientists
  7. 5. Strategies for Learning
  8. 6. Criteria of Learning
  9. 7. Inference of Approximations
  10. 8. Environments
  11. 9. Team and Probabilistic Learning
  12. 10. Learning with Additional Information
  13. 11. Learning with Oracles
  14. 12. Complexity Issues in Identification
  15. 13. Beyond Identification by Enumeration
  16. Bibliography
  17. Notation IndexX
  18. Author and Subject Index