Includes bibliographical references and index.

Preface to the Second Edition -- Preface to the First Edition -- Summary of Notation -- 1. Introduction -- I. Tabular Solution Methods -- II. Approximate Solution Methods -- III. Looking Deeper.

Available on-campus and off-campus.

"Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms."-- Provided by publisher.