You're reading from Deep Reinforcement Learning Hands-On Apply modern RL methods to practical problems of chatbots, robotics, discrete optimization, web automation, and more

Product type Paperback

Published in Jan 2020

Publisher Packt

ISBN-13 9781838826994

Length 826 pages

Edition 2nd Edition

Languages

Python

Tools

Deep Reinforcement Learning

Concepts

Chatbots

Author (1):

Maxim Lapan

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Table of Contents (28) Chapters

Preface

1. What Is Reinforcement Learning?

2. OpenAI Gym FREE CHAPTER

3. Deep Learning with PyTorch

4. The Cross-Entropy Method

5. Tabular Learning and the Bellman Equation

6. Deep Q-Networks

7. Higher-Level RL Libraries

8. DQN Extensions

9. Ways to Speed up RL

10. Stocks Trading Using RL

11. Policy Gradients – an Alternative

12. The Actor-Critic Method

13. Asynchronous Advantage Actor-Critic

14. Training Chatbots with RL

15. The TextWorld Environment

16. Web Navigation

17. Continuous Action Space

18. RL in Robotics

19. Trust Regions – PPO, TRPO, ACKTR, and SAC

20. Black-Box Optimization in RL

21. Advanced Exploration

22. Beyond Model-Free – Imagination

23. AlphaGo Zero

24. RL in Discrete Optimization

25. Multi-agent RL

26. Other Books You May Enjoy

27. Index

Basic DQN

To get started, we will implement the same DQN method as in Chapter 6, Deep Q-Networks, but leveraging the high-level libraries described in Chapter 7, Higher-Level RL Libraries. This will make our code much more compact, which is good, as non-relevant details won't distract us from the method's logic.

At the same time, the purpose of this book is not to teach you how to use the existing libraries, but rather how to develop intuition about RL methods and, if necessary, implement everything from scratch. From my perspective, this is a much more valuable skill, as libraries come and go, but true understanding of the domain will allow you to quickly make sense of other people's code and apply it consciously.

In the basic DQN implementation, we have three modules:

Chapter08/lib/dqn_model.py: the DQN neural network (NN), which is the same as Chapter 6, so I won't repeat it
Chapter08/lib/common.py: common functions and declarations shared by...