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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
Languages
Python
Tools
KerasTensorFlow
Concepts
Deep Reinforcement Learning
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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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OpenAI Universe

The core idea underlying OpenAI Universe (available at https://github.com/openai/universe) is to wrap general GUI applications into an RL environment using the same core classes provided by Gym. To achieve this, it uses the VNC protocol to connect with the VNC server running inside the Docker (a standard method running lightweight containers) container, exposing the mouse and keyboard actions to the RL agent and providing the GUI application image as an observation.

The reward is provided by an external small rewarder daemon running inside the same container and giving the agent the scalar reward value based on this rewarder judgement. It is possible to launch several containers locally, or over the network, to gather episodes data in parallel, in the same way that we started several Atari emulators to increase the convergence of the asynchronous advantage actor-critic (A3C) method in Chapter 13, Asynchronous Advantage Actor-Critic. The architecture is illustrated...

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Deep Reinforcement Learning Hands-On. - Second Edition
Published in: Jan 2020Publisher: PacktISBN-13: 9781838826994
© 2020 Packt Publishing Limited All Rights Reserved

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

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