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Hands-On Neuroevolution with Python.

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

Product type Book
Published in Dec 2019
Publisher Packt
ISBN-13 9781838824914
Pages 368 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Iaroslav Omelianenko Iaroslav Omelianenko
Profile icon Iaroslav Omelianenko
LinkedIn
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.
See other products by Iaroslav Omelianenko

Table of Contents (18) Chapters

Preface 1. Section 1: Fundamentals of Evolutionary Computation Algorithms and Neuroevolution Methods
2. Overview of Neuroevolution Methods 3. Python Libraries and Environment Setup 4. Section 2: Applying Neuroevolution Methods to Solve Classic Computer Science Problems
5. Using NEAT for XOR Solver Optimization 6. Pole-Balancing Experiments 7. Autonomous Maze Navigation 8. Novelty Search Optimization Method 9. Section 3: Advanced Neuroevolution Methods
10. Hypercube-Based NEAT for Visual Discrimination 11. ES-HyperNEAT and the Retina Problem 12. Co-Evolution and the SAFE Method 13. Deep Neuroevolution 14. Section 4: Discussion and Concluding Remarks
15. Best Practices, Tips, and Tricks 16. Concluding Remarks 17. Other Books You May Enjoy

Section 1: Fundamentals of Evolutionary Computation Algorithms and Neuroevolution Methods

This section introduces core concepts of evolutionary computation and discusses particulars of neuroevolution-based algorithms and which Python libraries can be used to implement them. You will become familiar with the fundamentals of neuroevolution methods and will get practical recommendations on how to start your experiments. This section provides a basic introduction to the Anaconda package manager for Python as part of your environment setup.

This section comprises the following chapters:

  • Chapter 1, Overview of Neuroevolution Methods
  • Chapter 2, Python Libraries and Environment Setup
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Hands-On Neuroevolution with Python.
Published in: Dec 2019 Publisher: Packt ISBN-13: 9781838824914
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Authors (1)

Profile icon Iaroslav Omelianenko
LinkedIn
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.
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See other products by Iaroslav Omelianenko

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