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PyTorch 1.x Reinforcement Learning Cookbook

You're reading from PyTorch 1.x Reinforcement Learning Cookbook

Product type Book

Published in Oct 2019

Publisher Packt

ISBN-13 9781838551964

Pages 340 pages

Edition 1st Edition

Languages

Concepts

Reinforcement Learning

Author (1):

Yuxi (Hayden) Liu

Table of Contents (11) Chapters

Preface

1. Getting Started with Reinforcement Learning and PyTorch

2. Markov Decision Processes and Dynamic Programming

3. Monte Carlo Methods for Making Numerical Estimations

4. Temporal Difference and Q-Learning

5. Solving Multi-armed Bandit Problems

6. Scaling Up Learning with Function Approximation

7. Deep Q-Networks in Action

8. Implementing Policy Gradients and Policy Optimization

9. Capstone Project – Playing Flappy Bird with DQN

10. Other Books You May Enjoy

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Solving the Taxi problem with SARSA

In this recipe, we will solve the Taxi environment with the SARSA algorithm and fine-tune the hyperparameters with the grid search algorithm.

We will start with our default set of hyperparameter values under the SARSA model. These are selected based on intuition and a number of trials. Moving on, we will come up with the best set of values.

How to do it...

We perform SARSA to solve the Taxi environment as follows:

Import PyTorch and the gym module, and create an instance of the Taxi environment:

>>> import torch
>>> import gym
>>> env = gym.make('Taxi-v2')

Then, start defining the epsilon-greedy behavior policy. We will reuse the gen_epsilon_greedy_policy...

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Authors (1)

Yuxi (Hayden) Liu

Yuxi (Hayden) Liu was a Machine Learning Software Engineer at Google. With a wealth of experience from his tenure as a machine learning scientist, he has applied his expertise across data-driven domains and applied his ML expertise in computational advertising, cybersecurity, and information retrieval. He is the author of a series of influential machine learning books and an education enthusiast. His debut book, also the first edition of Python Machine Learning by Example, ranked the #1 bestseller in Amazon and has been translated into many different languages.

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