December 2019
Intermediate to advanced
368 pages
11h 10m
English
Content preview from Hands-On Neuroevolution with Python
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What this book covers
Chapter 1, Overview of Neuroevolution Methods, introduces the core concepts of genetic algorithms, such as genetic operators and genome encoding schemes.
Chapter 2, Python Libraries and Environment Setup, discusses the practical aspects of neuroevolution methods. This chapter provides the pros and cons of popular Python libraries that provide implementations of the NEAT algorithm and its extensions.
Chapter 3, Using NEAT for XOR Solver Optimization, is where you start experimenting with the NEAT algorithm by implementing a solver for a classical computer science problem.
Chapter 4, Pole-Balancing Experiments, is where you continue with experiments related to the classic problems of computer science in the field of reinforcement ...
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