Galvan, Edgar and Mezura-Montes, Efrén and Elhara, Ouassim Ait and Schoenauer, Marc (2016) On the Use of Semantics in Multi-objective Genetic Programming. Parallel Problem Solving from Nature – PPSN XIV. pp. 353-363. ISSN 0302-9743

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Abstract

Research on semantics in Genetic Programming (GP) has increased dramatically over the last number of years. Results in this area clearly indicate that its use in GP can considerably increase GP performance. Motivated by these results, this paper investigates for the first time the use of Semantics in Muti-objective GP within the well-known NSGA-II algorithm. To this end, we propose two forms of incorporating semantics into a MOGP system. Results on challenging (highly) unbalanced binary classification tasks indicate that the adoption of semantics in MOGP is beneficial, in particular when a semantic distance is incorporated into the core of NSGA-II.

Item Type:	Article
Keywords:	Semantics; Multi-objective; Genetic Programming;
Academic Unit:	Faculty of Science and Engineering > Computer Science Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	15358
Identification Number:	https://doi.org/10.1007/978-3-319-45823-6
Depositing User:	Edgar Galvan
Date Deposited:	31 Jan 2022 12:08
Journal or Publication Title:	Parallel Problem Solving from Nature – PPSN XIV
Publisher:	Springer
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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