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Hands-On Neuroevolution with Python

You're reading from   Hands-On Neuroevolution with Python Build high-performing artificial neural network architectures using neuroevolution-based algorithms

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Product type Paperback
Published in Dec 2019
Publisher Packt
ISBN-13 9781838824914
Length 368 pages
Edition 1st Edition
Languages
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Author (1):
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Iaroslav Omelianenko Iaroslav Omelianenko
Author Profile Icon Iaroslav Omelianenko
Iaroslav Omelianenko
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Toc

Table of Contents (18) Chapters Close

Preface 1. Section 1: Fundamentals of Evolutionary Computation Algorithms and Neuroevolution Methods FREE CHAPTER
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

Maze navigation problem

The maze navigation problem is a classic computer science problem that is closely related to creating autonomous navigation agents that can find a path through ambiguous environments. The maze environment is an illustrative domain for the class of problems that have a deceptive fitness landscape. This means that the goal-oriented fitness function can have steep gradients of fitness scores in dead ends in the maze that are close to the final goal point. Such areas of the maze become the local optima for objective-based search algorithms that may converge in these areas. When the search algorithm converges in such deceptive local optima, it cannot find an adequate maze-solver agent.

In the following example, you can see a two-dimensional maze with local optima dead ends, which are shaded in:

The two-dimensional maze configuration

The maze configuration in...

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