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

Deep Reinforcement Learning: Fundamentals, Research and Applications

Springer

Reinforcement Learning: Theory and Python Implementation

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

Mathematical Foundations of Reinforcement Learning

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

Deep Reinforcement Learning with Python: RLHF for Chatbots and Large Language Models

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

Reinforcement Learning – An Introduction

MIT Press

Multi-Agent Reinforcement Learning: Foundations and Modern Approaches

MIT Press

An Introduction to Deep Reinforcement Learning

Chapman and Hall/CRC

Control Systems and Reinforcement Learning

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

Springer

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

Deep Learning with R

Springer

Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms

O'Reilly

Reinforcement Learning for Decision & Optimal Control - Springer

The Science of Deep Learning

Cambridge University Press

Fundamentals of Machine Learning and Deep Learning in Medicine

Springer

Reinforcement Learning for Sequential Decision and Optimal Control

Penguin Random House Deep Learning (Adaptive Computation and Machine Learning series)

MIT Press

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

Deep Learning: A Practical Introduction

Wiley

Introduction to Deep Learning: From Logical Calculus to Artificial Intelligence (Undergraduate Topics in Computer Science)

Springer

Mathematical Engineering of Deep Learning (Chapman & Hall/CRC Data Science Series)

Chapman and Hall/CRC