Chapter 1, Getting Started with Reinforcement Learning and PyTorch, is the starting point for readers who are looking forward to beginning this book's step-by-step guide to reinforcement learning with PyTorch. We will set up the working environment and OpenAI Gym and get familiar with reinforcement learning environments using the Atari and CartPole playgrounds. The chapter will also cover the implementation of several basic reinforcement learning algorithms, including random search, hill-climbing, and policy gradient. At the end, readers will also have a chance to review the essentials of PyTorch and get ready for the upcoming learning examples and projects.
Chapter 2, Markov Decision Process and Dynamic Programming ...
