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Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games

Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games develops its specific learning techniques, motivated by application to autonomous driving and microgrid systems, with breadth and depth: integral reinforcement learning (RL) achieves model-free control without system e...

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Bibliographic Details
Main Authors: Lian, Bosen, Xue, Wenqian (Author), Lewis, Frank L. (Author), Modares, Hamidreza (Author)
Format: eBook
Language:English
Published: Cham Springer Nature Switzerland 2024, 2024
Edition:1st ed. 2024
Series:Advances in Industrial Control
Subjects:
Engineering Mathematics
Computational Intelligence
Automotive Engineering
Control And Systems Theory
Control Engineering
Engineering / Data Processing
Mathematical And Computational Engineering Applications
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • 1. Introduction
  • 2. Background on Integral and Inverse Reinforcement Learning for Dynamic System Feedback
  • 3. Integral Reinforcement Learning for Optimal Regulation
  • 4. Integral Reinforcement Learning for Optimal Tracking
  • 5. Integral Reinforcement Learning for Nonlinear Tracker
  • Integral Reinforcement Learning for H-infinity Control
  • 6. Inverse Reinforcement Learning for Linear and Nonlinear Systems
  • 7. Inverse Reinforcement Learning for Two-Player Zero-Sum Games
  • 8. Inverse Reinforcement Learning for Multi-player Nonzero-sum Games

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