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Deep Reinforcement Learning in Action is Published

Our book Deep Reinforcement Learning in Action is out at Manning.com and will be out on Amazon once Amazon starts accepting new book shipments (has been delayed due to the covid19 pandemic). We hope you'll buy a copy and tell your friends and colleagues and leave us a review. We put a lot of work into this book and think it's one of the best ways to learn Deep Reinforcement Learning from the fundamentals to implementing some of the latest research papers.

Here's the table of contents:

PART 1: FOUNDATIONS

• 1 What Is Reinforcement Learning
• 2 Modeling Reinforcement Learning Problems: Markov Decision Processes
• 3 Predicting the Best States and Actions: Deep Q-Networks
• 4 Learning to Pick the Best Action: Policy Gradients
• 5 Tackling more Complex Environments with Actor-Critic Methods

PART 2: ABOVE AND BEYOND

• 6 Alternative Optimization Methods: Evolutionary Algorithms
• 7 Distributional DQN: Getting the full story
• 8 Curiosity-Driven Exploration
• 9 Multi-Agent Reinforcement Learning
• 10 Interpretable Reinforcement Learning: Attention and Relational Models
• 11 Conclusion

APPENDICES

• A Deep Learning, Mathematics, PyTorch

-Brandon