Book contents
- Frontmatter
- Dedication
- Contents
- Preface
- 1 Introduction
- Part I Fundamentals without Noise
- Part II Reinforcement Learning and Stochastic Control
- 6 Markov Chains
- 7 Stochastic Control
- 8 Stochastic Approximation
- 9 Temporal Difference Methods
- 10 Setting the Stage, Return of the Actors
- Appendices
- References
- Glossary of Symbols and Acronyms
- Index
9 - Temporal Difference Methods
from Part II - Reinforcement Learning and Stochastic Control
Published online by Cambridge University Press: 17 May 2022
Book contents
- Frontmatter
- Dedication
- Contents
- Preface
- 1 Introduction
- Part I Fundamentals without Noise
- Part II Reinforcement Learning and Stochastic Control
- 6 Markov Chains
- 7 Stochastic Control
- 8 Stochastic Approximation
- 9 Temporal Difference Methods
- 10 Setting the Stage, Return of the Actors
- Appendices
- References
- Glossary of Symbols and Acronyms
- Index
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- Control Systems and Reinforcement Learning , pp. 318 - 361Publisher: Cambridge University PressPrint publication year: 2022