Hands-On Reinforcement Learning for Games

Preface

This book is your one-stop shop for learning how various reinforcement learning (RL) techniques and algorithms play an important role in game development using Python.

The book will start with the basics to provide you with the necessary foundation to understand how RL is playing a major role in game development. Each chapter will help you implement various RL techniques, such as Markov decision processes, Q-learning, the actor-critic method, state-action-reward-state-action (SARSA), and the deterministic policy gradients algorithm, to build logical self-learning agents. You will use these techniques to enhance your game development skills and add various features to improve your overall productivity. Later in the book, you will learn ...