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You're reading from  Hands-On Reinforcement Learning with Python

Product typeBook
Published inJun 2018
Reading LevelIntermediate
PublisherPackt
ISBN-139781788836524
Edition1st Edition
Languages
Python
Tools
TensorFlowKeras
Concepts
Reinforcement Learning
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Author (1)
Sudharsan Ravichandiran
Sudharsan Ravichandiran
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Sudharsan Ravichandiran

Sudharsan Ravichandiran is a data scientist and artificial intelligence enthusiast. He holds a Bachelors in Information Technology from Anna University. His area of research focuses on practical implementations of deep learning and reinforcement learning including natural language processing and computer vision. He is an open-source contributor and loves answering questions on Stack Overflow.
Read more about Sudharsan Ravichandiran

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Summary

In this chapter, we learned about how the Monte Carlo method works and how can we use it to solve MDP when we don't know the model of the environment. We have looked at two different methods: one is Monte Carlo prediction, which is used for estimating the value function, and the other is Monte Carlo control, which is used for optimizing the value function.

We looked at two different methods in Monte Carlo prediction: first visit Monte Carlo prediction, where we average the return only the first time the state is visited in an episode, and the every visit Monte Carlo method, where we average the return every time the state is visited in an episode.

In terms of Monte Carlo control, we looked at different algorithms. We first encountered MC-ES control, which is used to cover all state-action pairs. We looked at on-policy MC control, which uses the epsilon-greedy policy...

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Hands-On Reinforcement Learning with Python
Published in: Jun 2018Publisher: PacktISBN-13: 9781788836524
© 2018 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Sudharsan Ravichandiran

Sudharsan Ravichandiran is a data scientist and artificial intelligence enthusiast. He holds a Bachelors in Information Technology from Anna University. His area of research focuses on practical implementations of deep learning and reinforcement learning including natural language processing and computer vision. He is an open-source contributor and loves answering questions on Stack Overflow.
Read more about Sudharsan Ravichandiran

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