Search icon
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
Free Learning
Arrow right icon
Deep Reinforcement Learning Hands-On. - Second Edition

You're reading from  Deep Reinforcement Learning Hands-On. - Second Edition

Product type Book
Published in Jan 2020
Publisher Packt
ISBN-13 9781838826994
Pages 826 pages
Edition 2nd Edition
Languages
Author (1):
Maxim Lapan Maxim Lapan
Profile icon Maxim Lapan

Table of Contents (28) Chapters

Preface What Is Reinforcement Learning? OpenAI Gym Deep Learning with PyTorch The Cross-Entropy Method Tabular Learning and the Bellman Equation Deep Q-Networks Higher-Level RL Libraries DQN Extensions Ways to Speed up RL Stocks Trading Using RL Policy Gradients – an Alternative The Actor-Critic Method Asynchronous Advantage Actor-Critic Training Chatbots with RL The TextWorld Environment Web Navigation Continuous Action Space RL in Robotics Trust Regions – PPO, TRPO, ACKTR, and SAC Black-Box Optimization in RL Advanced Exploration Beyond Model-Free – Imagination AlphaGo Zero RL in Discrete Optimization Multi-agent RL Other Books You May Enjoy
Index

Alternative ways of exploration

In this section, we will cover an overview of a set of alternative approaches to the exploration problem. This won't be an exhaustive list of approaches that exist, but rather will provide an outline of the landscape.

We're going to check three different approaches to exploration:

  • Randomness in the policy, when stochasticity is added to the policy that we use to get samples. The method in this family is noisy networks, which we have already covered.
  • Count-based methods, which keep track of the count of times the agent has seen the particular state. We will check two methods: the direct counting of states and the pseudo-count method.
  • Prediction-based methods, which try to predict something from the state and from the quality of the prediction. We can make judgements about the familiarity of the agent with this state. To illustrate this approach, we will take a look at the policy distillation method, which has shown state-of...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $15.99/month. Cancel anytime}