Handbook of Reinforcement Learning and Control / edited by Kyriakos G. Vamvoudakis, Yan Wan, Frank L. Lewis, Derya Cansever.

Format:

Book

Contributor:

Vamvoudakis, Kyriakos G., editor.

Series:

Studies in Systems, Decision and Control, 2198-4190 ; 325

Language:

English

Subjects (All):

Automatic control.

Multiagent systems.

Machine learning.

Data protection--Law and legislation.

Data protection.

Cooperating objects (Computer systems).

Control and Systems Theory.

Multiagent Systems.

Machine Learning.

Privacy.

Cyber-Physical Systems.

Local Subjects:

Control and Systems Theory.

Multiagent Systems.

Machine Learning.

Privacy.

Cyber-Physical Systems.

Physical Description:

1 online resource (839 pages)

Edition:

1st ed. 2021.

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2021.

Summary:

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. .

Contents:

The Cognitive Dialogue: A New Architecture for Perception and Cognition

Rooftop-Aware Emergency Landing Planning for Small Unmanned Aircraft Systems

Quantum Reinforcement Learning in Changing Environment

The Role of Thermodynamics in the Future Research Directions in Control and Learning

Mixed Density Reinforcement Learning Methods for Approximate Dynamic Programming

Analyzing and Mitigating Link-Flooding DoS Attacks Using Stackelberg Games and Adaptive Learning

Learning and Decision Making for Complex Systems Subjected to Uncertainties: A Stochastic Distribution Control Approach

Optimal Adaptive Control of Partially Unknown Linear Continuous-time Systems with Input and State Delay

Gradient Methods Solve the Linear Quadratic Regulator Problem Exponentially Fast

Architectures, Data Representations and Learning Algorithms: New Directions at the Confluence of Control and Learning

Reinforcement Learning for Optimal Feedback Control and Multiplayer Games

Fundamental Principles of Design for Reinforcement Learning Algorithms Course Titles

Long-Term Impacts of Fair Machine Learning

Learning-based Model Reduction for Partial Differential Equations with Applications to Thermo-Fluid Models' Identification, State Estimation, and Stabilization

CESMA: Centralized Expert Supervises Multi-Agents, for Decentralization

A Unified Framework for Reinforcement Learning and Sequential Decision Analytics

Trading Utility and Uncertainty: Applying the Value of Information to Resolve the Exploration-Exploitation Dilemma in Reinforcement Learning

Multi-Agent Reinforcement Learning: Recent Advances, Challenges, and Applications

Reinforcement Learning Applications, An Industrial Perspective

A Hybrid Dynamical Systems Perspective of Reinforcement Learning

Bounded Rationality and Computability Issues in Learning, Perception, Decision-Making, and Games Panagiotis Tsiotras

Mixed Modality Learning

Computational Intelligence in Uncertainty Quantification for Learning Control and Games

Reinforcement Learning Based Optimal Stabilization of Unknown Time Delay Systems Using State and Output Feedback

Robust Autonomous Driving with Humans in the Loop

Boundedly Rational Reinforcement Learning for Secure Control.

Notes:

Print version record.

ISBN:

3-030-60990-1

OCLC:

1257705186