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

Product typeBook
Published inOct 2019
Reading LevelIntermediate
PublisherPackt
ISBN-139781838551964
Edition1st Edition
Languages
Python
Tools
PyTorch
Concepts
Reinforcement Learning
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Author (1)
Yuxi (Hayden) Liu
Yuxi (Hayden) Liu
author image
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.
Read more about Yuxi (Hayden) Liu

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Creating a Markov chain

Let's get started by creating a Markov chain, on which the MDP is developed.

A Markov chain describes a sequence of events that comply with the Markov property. It is defined by a set of possible states, S = {s0, s1, ... , sm}, and a transition matrix, T(s, s'), consisting of the probabilities of state s transitioning to state s'. With the Markov property, the future state of the process, given the present state, is conditionally independent of past states. In other words, the state of the process at t+1 is dependent only on the state at t. Here, we use a process of study and sleep as an example and create a Markov chain based on two states, s0 (study) and s1 (sleep). Let's say we have the following transition matrix:

In the next section, we will compute the transition matrix after k steps, and the probabilities of being in each state...

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PyTorch 1.x Reinforcement Learning Cookbook
Published in: Oct 2019Publisher: PacktISBN-13: 9781838551964
© 2019 Packt Publishing Limited All Rights Reserved

Author (1)

author image
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.
Read more about Yuxi (Hayden) Liu

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