A Hierarchical Probabilistic Divergent Search Applied to a Binary Classification

Senthil Murugan, Enrique Naredo, Douglas Dias, Douglas Dias, Conor Ryan, Flaviano Godinez, James Patten

2022

Abstract

The trend in recent years of the scientific community on solving a wide range of problems through Artificial Intelligence has highlighted the benefits of open-ended search algorithms. In this paper we apply a probabilistic version for a divergent search algorithm in combination of a strategy to reduce the number of evaluations and computational effort by gathering the population from a Genetic Programming algorithm into groups and pruning the worst groups each certain number of generations. The combination proposed has shown encouraging results against a standard GP implementation on three binary classification problems, where the time taken to run an experiment is significantly reduced to only 5% of the total time from the standard approach while still maintaining, and indeed exceeding in the experimental results.

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Paper Citation


in Harvard Style

Murugan S., Naredo E., Dias D., Ryan C., Godinez F. and Patten J. (2022). A Hierarchical Probabilistic Divergent Search Applied to a Binary Classification. In Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-547-0, pages 345-353. DOI: 10.5220/0010841900003116


in Bibtex Style

@conference{icaart22,
author={Senthil Murugan and Enrique Naredo and Douglas Dias and Conor Ryan and Flaviano Godinez and James Patten},
title={A Hierarchical Probabilistic Divergent Search Applied to a Binary Classification},
booktitle={Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2022},
pages={345-353},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010841900003116},
isbn={978-989-758-547-0},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - A Hierarchical Probabilistic Divergent Search Applied to a Binary Classification
SN - 978-989-758-547-0
AU - Murugan S.
AU - Naredo E.
AU - Dias D.
AU - Ryan C.
AU - Godinez F.
AU - Patten J.
PY - 2022
SP - 345
EP - 353
DO - 10.5220/0010841900003116