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

View More author details

Table of Contents (22) Chapters

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

Finding the best advertisement banner using bandits

In this section, let's see how to find the best advertisement banner using bandits. Suppose we are running a website and we have five different banners for a single advertisement on our website, and say we want to figure out which advertisement banner is most liked by the users.

We can frame this problem as a MAB problem. The five advertisement banners represent the five arms of the bandit, and we assign +1 reward if the user clicks the advertisement and 0 reward if the user does not click the advertisement. So, to find out which advertisement banner is most clicked by the users, that is, which advertisement banner can give us the maximum reward, we can use various exploration strategies. In this section, let's just use an epsilon-greedy method to find the best advertisement banner.

First, let's import the necessary libraries:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import...

The rest of the chapter is locked

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

Table of Contents (22) Chapters

Finding the best advertisement banner using bandits

Authors (1)

Other recommended products

Personalised recommendations for you

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

Table of Contents (22) Chapters

Finding the best advertisement banner using bandits

Unlock this book and the full library FREE for 7 days

Authors (1)

Other recommended products

Personalised recommendations for you