Preface

This book will introduce the Q-learning algorithm using OpenAI Gym, TensorFlow, and Keras in a Python programming environment.

We will start by writing model-free Q-learning implementations to solve toy text problems and then learn how to use Q-networks and deep Q-networks to solve more complex problems. We will also learn how to tune and optimize Q-networks and their hyperparameters. Finally, we will discuss how Q-learning and related algorithms are used in real-world applications, such as scientific research and experimental design.

Use cases will include OpenAI Gym's Taxi and CartPole environments.