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Hands-On Neuroevolution with Python Cover

Hands-On Neuroevolution with Python

Build high-performing artificial neural network architectures using neuroevolution-based algorithms

Paid access
|Dec 2019
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Table of Contents

  1. Overview of Neuroevolution Methods
  2. Python Libraries and Environment Setup
  3. Using NEAT for XOR Solver Optimization
  4. Pole-Balancing Experiments
  5. Autonomous Maze Navigation
  6. Novelty Search Optimization Method
  7. Hypercube-Based NEAT for Visual Discrimination
  8. ES-HyperNEAT and the Retina Problem
  9. Co-Evolution and the SAFE Method
  10. Deep Neuroevolution
  11. Best Practices, Tips, and Tricks
  12. Concluding Remarks
PDF ISBN: 978-1-83882-200-2
Publisher: Packt Publishing Limited
Copyright owner: © 2019 Packt Publishing Limited
Publication date: 2019
Language: English
Pages: 368