You're reading from Deep Reinforcement Learning with Python Master classic RL, deep RL, distributional RL, inverse RL, and more with OpenAI Gym and TensorFlow

Product type Paperback

Published in Sep 2020

Publisher Packt

ISBN-13 9781839210686

Length 760 pages

Edition 2nd Edition

Languages

Python

Tools

Deep Reinforcement Learning

Concepts

Deep Reinforcement Learning

Author (1):

Sudharsan Ravichandiran

Preface

1. Fundamentals of Reinforcement Learning

2. A Guide to the Gym Toolkit FREE CHAPTER

3. The Bellman Equation and Dynamic Programming

4. Monte Carlo Methods

5. Understanding Temporal Difference Learning

6. Case Study – The MAB Problem

7. Deep Learning Foundations

8. A Primer on TensorFlow

9. Deep Q Network and Its Variants

10. Policy Gradient Method

11. Actor-Critic Methods – A2C and A3C

12. Learning DDPG, TD3, and SAC

13. TRPO, PPO, and ACKTR Methods

14. Distributional Reinforcement Learning

15. Imitation Learning and Inverse RL

16. Deep Reinforcement Learning with Stable Baselines

17. Reinforcement Learning Frontiers

18. Other Books You May Enjoy

19. Index

Appendix 1 – Reinforcement Learning Algorithms

1. Appendix 2 – Assessments

Chapter 16 – Deep Reinforcement Learning with Stable Baselines

Stable Baselines is an improved implementation of OpenAI Baselines. Stable Baselines is a high-level library that is easier to use than OpenAI Baselines, and it also includes state-of-the-art deep RL algorithms along with offering several useful features.
We can save the agent as agent.save() and load the trained agent as agent.load().
We generally train our agent in a single environment per step but with Stable Baselines, we can train our agent in multiple environments per step. This helps our agent to learn quickly. Now, our states, actions, reward, and done will be in the form of a vector since we are training our agent in multiple environments. So, we call this a vectorized environment.
In SubprocVecEnv, we run each environment in a different process, whereas in DummyVecEnv, we run each environment in the same process.
With Stable Baselines, it is easier to view the computational...