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Multi-player H∞ Differential Game Using On-policy and Off-policy Reinforcement Learning

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Release : 2022
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Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Multi-player H∞ Differential Game Using On-policy and Off-policy Reinforcement Learning by : Peiliang An

Download or read book Multi-player H∞ Differential Game Using On-policy and Off-policy Reinforcement Learning written by Peiliang An. This book was released on 2022. Available in PDF, EPUB and Kindle. Book excerpt: This work studies a multi-player H∞ differential game for systems of general linear dynamics. In this game, multiple players design their control inputs to minimize their cost functions in the presence of worst-case disturbances. We first derive the optimal control and disturbance policies using the solutions to Hamilton-Jacobi-Isaacs (HJI) equations. We then prove that the derived optimal policies stabilize the system and constitute a Nash equilibrium solution. Two integral reinforcement learning (IRL) -based algorithms, including the policy iteration IRL and off-policy IRL, are developed to solve the differential game online. We show that the off-policy IRL can solve the multi-player H∞ differential game online without using any system dynamics information. Simulation studies are conducted to validate the theoretical analysis and demonstrate the effectiveness of the developed learning algorithms.

Reinforcement Learning

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Release : 2023-07-24
Genre : Technology & Engineering
Kind : eBook
Book Rating : 945/5 ( reviews)

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Book Synopsis Reinforcement Learning by : Jinna Li

Download or read book Reinforcement Learning written by Jinna Li. This book was released on 2023-07-24. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a thorough introduction to the basics and scientific and technological innovations involved in the modern study of reinforcement-learning-based feedback control. The authors address a wide variety of systems including work on nonlinear, networked, multi-agent and multi-player systems. A concise description of classical reinforcement learning (RL), the basics of optimal control with dynamic programming and network control architectures, and a brief introduction to typical algorithms build the foundation for the remainder of the book. Extensive research on data-driven robust control for nonlinear systems with unknown dynamics and multi-player systems follows. Data-driven optimal control of networked single- and multi-player systems leads readers into the development of novel RL algorithms with increased learning efficiency. The book concludes with a treatment of how these RL algorithms can achieve optimal synchronization policies for multi-agent systems with unknown model parameters and how game RL can solve problems of optimal operation in various process industries. Illustrative numerical examples and complex process control applications emphasize the realistic usefulness of the algorithms discussed. The combination of practical algorithms, theoretical analysis and comprehensive examples presented in Reinforcement Learning will interest researchers and practitioners studying or using optimal and adaptive control, machine learning, artificial intelligence, and operations research, whether advancing the theory or applying it in mineral-process, chemical-process, power-supply or other industries.

Handbook of Reinforcement Learning and Control

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Release : 2021-06-23
Genre : Technology & Engineering
Kind : eBook
Book Rating : 901/5 ( reviews)

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Book Synopsis Handbook of Reinforcement Learning and Control by : Kyriakos G. Vamvoudakis

Download or read book Handbook of Reinforcement Learning and Control written by Kyriakos G. Vamvoudakis. This book was released on 2021-06-23. Available in PDF, EPUB and Kindle. Book excerpt: This handbook presents state-of-the-art research in reinforcement learning, focusing on its applications in the control and game theory of dynamic systems and future directions for related research and technology. The contributions gathered in this book deal with challenges faced when using learning and adaptation methods to solve academic and industrial problems, such as optimization in dynamic environments with single and multiple agents, convergence and performance analysis, and online implementation. They explore means by which these difficulties can be solved, and cover a wide range of related topics including: deep learning; artificial intelligence; applications of game theory; mixed modality learning; and multi-agent reinforcement learning. Practicing engineers and scholars in the field of machine learning, game theory, and autonomous control will find the Handbook of Reinforcement Learning and Control to be thought-provoking, instructive and informative.

Neural Networks for Control

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Release : 1995
Genre : Computers
Kind : eBook
Book Rating : 617/5 ( reviews)

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Book Synopsis Neural Networks for Control by : W. Thomas Miller

Download or read book Neural Networks for Control written by W. Thomas Miller. This book was released on 1995. Available in PDF, EPUB and Kindle. Book excerpt: Neural Networks for Control brings together examples of all the most important paradigms for the application of neural networks to robotics and control. Primarily concerned with engineering problems and approaches to their solution through neurocomputing systems, the book is divided into three sections: general principles, motion control, and applications domains (with evaluations of the possible applications by experts in the applications areas.) Special emphasis is placed on designs based on optimization or reinforcement, which will become increasingly important as researchers address more complex engineering challenges or real biological-control problems.A Bradford Book. Neural Network Modeling and Connectionism series

Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games

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Kind : eBook
Book Rating : 526/5 ( reviews)

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Book Synopsis Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games by : Bosen Lian

Download or read book Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games written by Bosen Lian. This book was released on . Available in PDF, EPUB and Kindle. Book excerpt:

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