Systems That Learn, Second Edition

From Learning, Development, and Conceptual Change

Systems That Learn, Second Edition

An Introduction to Learning Theory

By Sanjay Jain, Daniel N. Osherson, James S. Royer and Arun Sharma

Bradford Books





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.

Bradford Books imprint


$50.00 X ISBN: 9780262100779 329 pp. | 7.3 in x 9 in


  • The most thorough book on learning theory I have ever seen. This book is bound to be on every researcher's table.

    Rusins Freivalds

    University of Latvia

  • Systems That Learn is an important updating of the book by Osherson, Stob and Weinstein that introduced formal learning theory to a wide audience of philosophers, linguists, psychologists and logicians. The field has progressed, and the same audience will find much that is new and amazing in this second edition by Jain, Osherson, royer and Sharma.

    Clark Glymour

    Alumni University Professor, Carnegie Mellon University; and Valtz Family Professor, University of California

  • The new edition of Systems That Learn is an outstanding work - it provides a lucid and self-contained introduction to the rigorous investigation of learning and scientific discovery.

    Scott Weinstein

    Department of Philosophy, University of Pennsylvania

  • This book is a beautifully written, excellent introduction to a number of central topics in the theory of learning. I warmly recommend it to anyone interested in this challenging field.

    Rolf Wiehagen

    Professor of Computer Science, University of Kaiserslautern

  • This awaited second edition expands and imporves on the classic first edition.

    John Case

    Computer and Information Sciences Department, University of Delaware