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

Product typeBook

Published inJan 2020

Reading LevelIntermediate

PublisherPackt

ISBN-139781838826994

Edition2nd Edition

Languages

Python

Tools

Keras TensorFlow

Concepts

Deep Reinforcement Learning

Author (1)

Maxim Lapan

The PTAN library

The library is available in GitHub: https://github.com/Shmuma/ptan. All the subsequent examples were implemented using version 0.6 of PTAN, which can be installed in your virtual environment by running the following:

pip install ptan==0.6

The original goal of PTAN was to simplify my RL experiments, and it tries to keep the balance between two extremes:

Import the library and then write one line with tons of parameters to train one of the provided methods, like DQN (a very vivid example is the OpenAI Baselines project)
Implement everything from scratch

The first approach is very inflexible. It works well when you are using the library the way it is supposed to be used. But if you want to do something fancy, you will quickly find yourself hacking the library and fighting with the constraints that I imposed, rather than solving the problem you want to solve.

The second extreme gives too much freedom and requires implementing replay buffers...

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Deep Reinforcement Learning Hands-On. - Second Edition

Published in: Jan 2020Publisher: PacktISBN-13: 9781838826994

Author (1)

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

The PTAN library

Unlock this book and the full library FREE for 7 days

Author (1)

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