Reinforcement Learning for Sequential Decision and Optimal Control

Have you ever wondered how AlphaZero learns to defeat the top human Go players? Do you have any clues about how an autonomous driving system can gradually develop self-driving skills beyond normal drivers? What is the key that enables AlphaStar to make decisions in Starcraft, a notoriously difficult...

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Bibliographic Details
Main Author:	Li, Shengbo Eben (Author)
Corporate Author:	SpringerLink (Online service)
Format:	Electronic eBook
Language:	English
Published:	Singapore : Springer Nature Singapore : Imprint: Springer, 2023.
Edition:	1st ed. 2023.
Subjects:	Machine learning. Computational intelligence. System theory. Control theory. Engineering mathematics. Control engineering. Robotics. Automation. Machine Learning. Computational Intelligence. Systems Theory, Control. Engineering Mathematics. Control, Robotics, Automation.
Online Access:	https://doi.org/10.1007/978-981-19-7784-8
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Table of Contents:

Chapter 1 Introduction of Reinforcement Learning
Chapter 2 Principles of RL Problems
Chapter 3 Model-free Indirect RL: Monte Carlo
Chapter 4 Model-Free Indirect RL: Temporal-Difference
Chapter 5 Model-based Indirect RL: Dynamic Programming
Chapter 6 Indirect RL with Function Approximation
Chapter 7 Direct RL with Policy Gradient
Chapter 8 Infinite Horizon Approximate Dynamic Programming
Chapter 9 Finite Horizon ADP and State Constraints
Chapter 10 Deep Reinforcement Learning
Chapter 11 Advanced RL Topics.

Reinforcement Learning for Sequential Decision and Optimal Control

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