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You're reading from  Hands-On Neuroevolution with Python.

Product typeBook
Published inDec 2019
Reading LevelExpert
PublisherPackt
ISBN-139781838824914
Edition1st Edition
Languages
Python
Concepts
Neural Networks
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Author (1)
Iaroslav Omelianenko
Iaroslav Omelianenko
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Iaroslav Omelianenko

Iaroslav Omelianenko occupied the position of CTO and research director for more than a decade. He is an active member of the research community and has published several research papers at arXiv, ResearchGate, Preprints, and more. He started working with applied machine learning by developing autonomous agents for mobile games more than a decade ago. For the last 5 years, he has actively participated in research related to applying deep machine learning methods for authentication, personal traits recognition, cooperative robotics, synthetic intelligence, and more. He is an active software developer and creates open source neuroevolution algorithm implementations in the Go language.
Read more about Iaroslav Omelianenko

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Training an agent to play the Frostbite game

Now that we have discussed the theory behind the game-playing agent's implementation, we are ready to start working on it. Our implementation is based on the source code provided by the Uber AI Lab on GitHub at https://github.com/uber-research/deep-neuroevolution. The source code in this repository contains an implementation of two methods to train DNNs: the CPU-based methods for multicore systems (up to 720 cores) and the GPU-based methods. We are interested in the GPU-based implementation because the majority of practitioners don't have access to such behemoths of technology as a PC with 720 CPU cores. At the same time, it is pretty easy to get access to a modern Nvidia GPU.

Next, we'll discuss the implementation details.

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Hands-On Neuroevolution with Python.
Published in: Dec 2019Publisher: PacktISBN-13: 9781838824914
© 2019 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Iaroslav Omelianenko

Iaroslav Omelianenko occupied the position of CTO and research director for more than a decade. He is an active member of the research community and has published several research papers at arXiv, ResearchGate, Preprints, and more. He started working with applied machine learning by developing autonomous agents for mobile games more than a decade ago. For the last 5 years, he has actively participated in research related to applying deep machine learning methods for authentication, personal traits recognition, cooperative robotics, synthetic intelligence, and more. He is an active software developer and creates open source neuroevolution algorithm implementations in the Go language.
Read more about Iaroslav Omelianenko

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