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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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Exercises

  1. Try to increase the value of the node_add_prob parameter and see what happens. Does the algorithm produce any number of hidden nodes, and if so, how many?
  2. Try to decrease/increase the compatibility_threshold value. What happens if you set it to 2.0 or 6.0? Can the algorithm find the solution in each case?
  3. Try to set the elitism value to zero in the DefaultReproduction section. See what happens. How long did the evolutionary process take to find an acceptable solution in this case?
  4. Set the survival_threshold value to 0.5 in the DefaultReproduction section. See how this affects speciation during evolution. Why does it?
  5. Increase the additional_num_runs and additional_steps values in order of magnitude to examine further how well the found control strategy is generalized. Is the algorithm still able to find a winning solution?
The last exercise will lead to an increase...
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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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