Reinforcement Learning: An Introduction

Book Next: Contents Contents Reinforcement learning : An Introduction Richard S. Sutton and Andrew G. Barto A Bradford Book The MIT Press Cambridge, Massachusetts London, England In memory of A. Harry Klopf l Contents m Preface m Series Forward m Summary of Notation l I. The Problem m 1. Introduction n Reinforcement learning (1 di 4)22/06/2005 Examples n Elements of Reinforcement learning n An Extended Example: Tic-Tac-Toe n Summary n History of Reinforcement learning n Bibliographical Remarks m 2. Evaluative Feedback n An -Armed Bandit Problem n Action-Value Methods n Softmax Action Selection n Evaluation Versus Instruction n Incremental Implementation n Tracking a Nonstationary Problem n Optimistic Initial Values n Reinforcement Comparison n Pursuit Methods n Associative Search n Conclusions n Bibliographical and Historical Remarks m 3.

While reinforcement learning had clearly motivated some of the earliest computational studies of learning, most of these researchers had gone on to other things, such as pattern classification, supervised learning, and adaptive control, or they had abandoned the study of

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