Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more: Maxim Lapan: 9781788834247: Amazon.com: Books

When I started learning RL three years ago, it was really hard to get practical information about the methods and ways that they could be implemented. Sparse blog posts about individual methods and theoretical papers, without code examples, were the only source of knowledge. To get something to experiment with, lots of time and effort was needed, fighting with weird bugs and misunderstanding mystic math in papers. With the rising popularity of RL, the situation has improved slightly, but, still, there is a lack of structured overview of the modern deep RL methods with a unified code base. This book fills the gap between theory and practice, providing a structured overview of recent RL methods, using clear examples written in uniform style.