Reader small image

You're reading from  Hands-On Neuroevolution with Python.

Product typeBook
Published inDec 2019
Reading LevelExpert
PublisherPackt
ISBN-139781838824914
Edition1st Edition
Languages
Right arrow
Author (1)
Iaroslav Omelianenko
Iaroslav Omelianenko
author image
Iaroslav Omelianenko

Iaroslav Omelianenko occupied the position of CTO and research director for more than a decade. He is an active member of the research community and has published several research papers at arXiv, ResearchGate, Preprints, and more. He started working with applied machine learning by developing autonomous agents for mobile games more than a decade ago. For the last 5 years, he has actively participated in research related to applying deep machine learning methods for authentication, personal traits recognition, cooperative robotics, synthetic intelligence, and more. He is an active software developer and creates open source neuroevolution algorithm implementations in the Go language.
Read more about Iaroslav Omelianenko

Right arrow

Hyperparameter selection

The XOR experiment we will discuss in this chapter uses the NEAT-Python library as a framework. The NEAT-Python library defines a set of hyperparameters that are used to control the execution and performance of the NEAT algorithm. The configuration file is stored in a format similar to Windows .INI files; each section starts with a name in square brackets ([section]), followed by key-value pairs that are delimited by an equals sign (=).

In this section, we will discuss some hyperparameters of the NEAT-Python library that can be found in each section of the configuration file.

A full list of the hyperparameters in the NEAT-Python library can be found at https://neat-python.readthedocs.io/en/latest/config_file.html.

NEAT section

...
lock icon
The rest of the page is locked
Previous PageNext Page
You have been reading a chapter from
Hands-On Neuroevolution with Python.
Published in: Dec 2019Publisher: PacktISBN-13: 9781838824914

Author (1)

author image
Iaroslav Omelianenko

Iaroslav Omelianenko occupied the position of CTO and research director for more than a decade. He is an active member of the research community and has published several research papers at arXiv, ResearchGate, Preprints, and more. He started working with applied machine learning by developing autonomous agents for mobile games more than a decade ago. For the last 5 years, he has actively participated in research related to applying deep machine learning methods for authentication, personal traits recognition, cooperative robotics, synthetic intelligence, and more. He is an active software developer and creates open source neuroevolution algorithm implementations in the Go language.
Read more about Iaroslav Omelianenko