deep reinforcement learning hands-on pdf github

eBook: Deep Reinforcement Learning Hands-On: Apply Modern RL Methods, with Deep Q-networks, Value Iteration, Policy Gradients, TRPO, AlphaGo Zero and More by Maxim Lapan

What You'll Learn:

Understand the DL context of RL and implement complex DL models

Learn the foundation of RL: Markov decision processes

Evaluate RL methods including Cross-entropy, DQN, Actor-Critic, TRPO, PPO, DDPG, D4PG and others

Discover how to deal with discrete and continuous action spaces in various environments

Defeat Atari arcade games using the value iteration method

Create your own OpenAI Gym environment to train a stock trading agent

Teach your agent to play Connect4 using AlphaGo Zero

Explore the very latest deep RL research on topics including AI-driven chatbots

And More....


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