Book contents
- Frontmatter
- Dedication
- Contents
- Preface
- 1 Introduction
- Part I Fundamentals without Noise
- 2 Control Crash Course
- 3 Optimal Control
- 4 ODE Methods for Algorithm Design
- 5 Value Function Approximations
- Part II Reinforcement Learning and Stochastic Control
- Appendices
- References
- Glossary of Symbols and Acronyms
- Index
5 - Value Function Approximations
from Part I - Fundamentals without Noise
Published online by Cambridge University Press: 17 May 2022
Book contents
- Frontmatter
- Dedication
- Contents
- Preface
- 1 Introduction
- Part I Fundamentals without Noise
- 2 Control Crash Course
- 3 Optimal Control
- 4 ODE Methods for Algorithm Design
- 5 Value Function Approximations
- Part II Reinforcement Learning and Stochastic Control
- Appendices
- References
- Glossary of Symbols and Acronyms
- Index
Summary
A summary is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
- Type
- Chapter
- Information
- Control Systems and Reinforcement Learning , pp. 159 - 202Publisher: Cambridge University PressPrint publication year: 2022