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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
Author (1):
Iaroslav Omelianenko Iaroslav Omelianenko
Profile icon Iaroslav Omelianenko

Table of Contents (18) Chapters

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

Suitable Python libraries for neuroevolution experiments

The Python programming language is one of the most popular languages for activities related to machine learning and research and development in the field of artificial intelligence. The most prominent frameworks are either written in Python or provide corresponding interfaces. Such popularity can be explained by Python's short learning curve and its nature as a scriptable language, which allows experiments to take place quickly. Thus, following a general trend in the machine learning community, several libraries were written in Python with the support for neuroevolution, and the number of libraries continues to grow over time. In this section, we will look at the most stable Python libraries for experiments in the field of evolutionary algorithms.

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