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

Product typeBook
Published inJan 2020
Reading LevelIntermediate
PublisherPackt
ISBN-139781838826994
Edition2nd Edition
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Author (1)
Maxim Lapan
Maxim Lapan
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Maxim Lapan

Maxim has been working as a software developer for more than 20 years and was involved in various areas: distributed scientific computing, distributed systems and big data processing. Since 2014 he is actively using machine and deep learning to solve practical industrial tasks, such as NLP problems, RL for web crawling and web pages analysis. He has been living in Germany with his family.
Read more about Maxim Lapan

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Summary

In this chapter, you became familiar with the cross-entropy method, which is simple but quite powerful, despite its limitations. We applied it to a CartPole environment (with huge success) and to FrozenLake (with much more modest success). In addition, we discussed the taxonomy of RL methods, which will be referenced many times during the rest of the book, as different approaches to RL problems have different properties, which influences their applicability.

This chapter ends the introductory part of the book. In the next part, we will switch to a more systematic study of RL methods and discuss the value-based family of methods. In upcoming chapters, we will explore more complex, but more powerful, tools of deep RL.

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Deep Reinforcement Learning Hands-On. - Second Edition
Published in: Jan 2020Publisher: PacktISBN-13: 9781838826994

Author (1)

author image
Maxim Lapan

Maxim has been working as a software developer for more than 20 years and was involved in various areas: distributed scientific computing, distributed systems and big data processing. Since 2014 he is actively using machine and deep learning to solve practical industrial tasks, such as NLP problems, RL for web crawling and web pages analysis. He has been living in Germany with his family.
Read more about Maxim Lapan