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Reinforcement Learning: An Introduction

IReinforcement Learning: An IntroductionSecond edition, in progressRichard S. Sutton and Andrew G. Bartoc 2014, 2015A Bradford BookThe MIT PressCambridge, MassachusettsLondon, EnglandiiIn memory of A. Harry KlopfContentsPreface ..viiiSeries Forward ..xiiSummary of Notation ..xiii1 The Reinforcement learning Reinforcement learning .. Examples .. Elements of Reinforcement learning .. Limitations and Scope .. An Extended Example: Tic-Tac-Toe .. Summary .. History of Reinforcement learning .. Bibliographical Remarks ..25I Tabular Solution Methods272 Multi-arm Ann-Armed Bandit Problem .. Action-Value Methods .. Incremental Implementation .. Tracking a Nonstationary Problem .. Optimistic Initial Values.

Reinforcement learning has gradually become one of the most active research areas in machine learning, arti cial intelligence, and neural net-work research. The eld has developed strong mathematical foundations and impressive applications. The computational study of reinforcement learning is

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