Reinforcement Learning: Optimal Feedback Control with Industrial Applications (Advances in Industrial Control)

Control Systems and Reinforcement Learning

Mathematical Foundations of Reinforcement Learning

Output Feedback Reinforcement Learning Control for Linear Systems (Control Engineering)

Reinforcement Learning: Theory and Python Implementation

Springer - Reinforcement Learning for Optimal Feedback Control

Springer

Deep Reinforcement Learning and Its Industrial Use Cases: AI for Real-World Applications

Deep Reinforcement Learning Hands-On: A practical and easy-to-follow guide to RL from Q-learning and DQNs to PPO and RLHF

Packt Publishing

Multi-Agent Reinforcement Learning: Foundations and Modern Approaches

MIT Press

Reinforcement Learning – An Introduction

MIT Press

The Art of Reinforcement Learning: Fundamentals, Mathematics, and Implementations with Python

Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games (Advances in Industrial Control)

Frontiers Of Intelligent Control And Information Processing

World Scientific Publishing Company

Reinforcement Learning for Decision & Optimal Control - Springer

Reinforcement Learning for Sequential Decision and Optimal Control

Human-Robot Interaction Control Using Reinforcement Learning (IEEE Press Series on Systems Science and Engineering)

Wiley-IEEE Press

Reinforcement Learning and Dynamic Programming Using Function Approximators: 39 (Automation and Control Engineering)

CRC Press

Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning: 55 (Operations Research/Computer Science Interfaces Series, 55)

Springer

Foundations of Reinforcement Learning with Applications in Finance (Chapman & Hall/CRC Mathematics and Artificial Intelligence Series)

CRC Press

Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning: 55 (Operations Research/Computer Science Interfaces Series, 55)

Springer

Model-based Reinforcement Learning: A Survey (Foundations and Trends® in Machine Learning)

Deep Reinforcement Learning: Fundamentals, Research and Applications

Springer

An Introduction to Deep Reinforcement Learning (Foundations and Trends (R) in Machine Learning)

Now Publishers

Decision Making Under Uncertainty and Reinforcement Learning: Theory and Algorithms: 223 (Intelligent Systems Reference Library, 223)

Springer

Reinforcement and Systemic Machine Learning for Decision Making (IEEE Press Series on Systems Science and Engineering)

Wiley-IEEE Press