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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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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

The single-pole balancing problem

The single-pole balancer (or inverted pendulum) is an unstable pendulum that has its center of mass above its pivot point. It can be stabilized by applying external forces under the control of a specialized system that monitors the angle of the pole and moves the pivot point horizontally back and forth under the center of mass as it starts to fall. The single-pole balancer is a classic problem in dynamics and control theory that is used as a benchmark for testing control strategies, including strategies based on reinforcement learning methods. We are particularly interested in the implementation of the specific control algorithm that uses neuroevolution-based methods to stabilize the inverted pendulum for a given amount of time.

The experiment described in this chapter considers the simulation of the inverted pendulum implemented as a cart that...

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