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Authors: Mauro Castelli 1 ; Luca Manzoni 2 ; Ivo Gonçalves 3 ; Leonardo Vanneschi 1 ; Leonardo Trujillo 4 and Sara Silva 5

Affiliations: 1 Universidade Nova de Lisboa, Portugal ; 2 Universitá degli Studi di Milano Bicocca, Italy ; 3 Universidade Nova de Lisboa and University of Coimbra, Portugal ; 4 Instituto Tecnológico de Tijuana, Mexico ; 5 University of Lisbon and University of Coimbra, Portugal

ISBN: 978-989-758-201-1

Keyword(s): Genetic Programming, Semantics, Convex Hull.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computational Intelligence ; Evolutionary Computing ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Soft Computing ; Symbolic Systems

Abstract: Geometric semantic operators have recently shown their ability to outperform standard genetic operators on different complex real world problems. Nonetheless, they are affected by drawbacks. In this paper, we focus on one of these drawbacks, i.e. the fact that geometric semantic crossover has often a poor impact on the evolution. Geometric semantic crossover creates an offspring whose semantics stands in the segment joining the parents (in the semantic space). So, it is intuitive that it is not able to find, nor reasonably approximate, a globally optimal solution, unless the semantics of the individuals in the population ``contains'' the target. In this paper, we introduce the concept of convex hull of a genetic programming population and we present a method to calculate the distance from the target point to the convex hull. Then, we give experimental evidence of the fact that, in four different real-life test cases, the target is always outside the convex hull. As a consequence, we show that geometric semantic crossover is not helpful in those cases, and it is not even able to approximate the population to the target. Finally, in the last part of the paper, we propose ideas for future work on how to improve geometric semantic crossover. (More)

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Paper citation in several formats:
Castelli, M.; Manzoni, L.; Gonçalves, I.; Vanneschi, L.; Trujillo, L. and Silva, S. (2016). An Analysis of Geometric Semantic Crossover: A Computational Geometry Approach.In Proceedings of the 8th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2016) ISBN 978-989-758-201-1, pages 201-208. DOI: 10.5220/0006056402010208

@conference{ecta16,
author={Mauro Castelli. and Luca Manzoni. and Ivo Gon\c{C}alves. and Leonardo Vanneschi. and Leonardo Trujillo. and Sara Silva.},
title={An Analysis of Geometric Semantic Crossover: A Computational Geometry Approach},
booktitle={Proceedings of the 8th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2016)},
year={2016},
pages={201-208},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006056402010208},
isbn={978-989-758-201-1},
}

TY - CONF

JO - Proceedings of the 8th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2016)
TI - An Analysis of Geometric Semantic Crossover: A Computational Geometry Approach
SN - 978-989-758-201-1
AU - Castelli, M.
AU - Manzoni, L.
AU - Gonçalves, I.
AU - Vanneschi, L.
AU - Trujillo, L.
AU - Silva, S.
PY - 2016
SP - 201
EP - 208
DO - 10.5220/0006056402010208

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