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

Deep Reinforcement Learning: Fundamentals, Research and Applications

Springer

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

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

Multi-Agent Reinforcement Learning: Foundations and Modern Approaches

MIT Press

Reinforcement Learning for Decision & Optimal Control - Springer

Reinforcement Learning for Sequential Decision and Optimal Control

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

CRC Press

Deep Reinforcement Learning in Unity: With Unity ML Toolkit

Apress

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

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

Reinforcement Learning: Theory and Python Implementation

Mathematical Foundations of Reinforcement Learning

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

Reinforcement Learning – An Introduction

MIT Press

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

Wiley-IEEE Press

Recent Advances in Soft Computing and Cybernetics: 403 (Studies in Fuzziness and Soft Computing, 403)

Springer

Hands-On Artificial Intelligence for Beginners: An introduction to AI concepts, algorithms, and their implementation

Packt Publishing

Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow

Packt Publishing

Artificial Intelligence with Python (Machine Learning: Foundations, Methodologies, and Applications)

Springer

Neural Networks and Deep Learning: A Textbook

Springer

Control Systems and Reinforcement Learning

AI Agent Frameworks: Technical Insights and Practical Applications.

Majosta

Algorithms for Decision Making

Understanding Deep Learning: Building Machine Learning Systems with PyTorch and TensorFlow: From Neural Networks (CNN, DNN, GNN, RNN, ANN, LSTM, GAN) to Natural Language Processing (NLP)