Nguyen, Quang Uy and O'Neill, Michael and Xuan Hoai, Nguyen and McKay, Bob and Galvan, Edgar (2009) Semantic Aware Crossover for Genetic Programming: The Case for Real-Valued Function Regression. Lecture Notes in Computer Science, 5481. pp. 292-302. ISSN 0302-9743

Preview

Download (277kB) | Preview

Abstract

In this paper, we apply the ideas from [2] to investigate the effect of some semantic based guidance to the crossover operator of GP. We conduct a series of experiments on a family of real-valued symbolic regression problems, examining four different semantic aware crossover operators. One operator considers the semantics of the exchanged subtrees, while the other compares the semantics of the child trees to their parents. Two control operators are adopted which reverse the logic of the semantic equivalence test. The results show that on the family of test problems examined, the (approximate) semantic aware crossover operators can provide performance advantages over the standard subtree crossover adopted in Genetic Programming.

Item Type:	Article
Keywords:	Semantic Similarity; Based Crossover; GP; Real-Valued; Function; Regression;
Academic Unit:	Faculty of Science and Engineering > Computer Science Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	15427
Identification Number:	https://doi.org/10.1007/978-3-642-01181-8_25
Depositing User:	Edgar Galvan
Date Deposited:	07 Feb 2022 15:52
Journal or Publication Title:	Lecture Notes in Computer Science
Publisher:	Springer Verlag
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

Repository Staff Only(login required)

Item control page

Downloads

Origin of downloads