Galvan-Lopez, Edgar and Cody-Kenny, Brendan and Trujillo, Leonardo and Kattan, Ahmed (2013) Using semantics in the selection mechanism in Genetic Programming: A simple method for promoting semantic diversity. IEEE Transactions on Evolutionary Computation. pp. 2972-2979. ISSN 1941-0026

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Abstract

Research on semantics in Genetic Programming (GP) has increased over the last number of years. Results in this area clearly indicate that its use in GP considerably increases performance. Many of these semantic-based approaches rely on a trial-and-error method that attempts to find offspring that are semantically different from their parents over a number of trials using the crossover operator (crossover-semantics based - CSB). This, in consequence, has a major drawback: these methods could evaluate thousands of nodes, resulting in paying a high computational cost, while attempting to improve performance by promoting semantic diversity. In this work, we propose a simple and computationally inexpensive method, named semantics in selection, that eliminates the computational cost observed in CSB approaches. We tested this approach in 14 GP problems, including continuous- and discrete-valued fitness functions, and compared it against a traditional GP and a CSB approach. Our results are equivalent, and in some cases, superior than those found by the CSB approach, without the necessity of using a “brute force” mechanism.

Item Type:	Article
Keywords:	Using semantics; selection mechanism; Genetic Programming; simple method; promoting; semantic diversity;
Academic Unit:	Faculty of Science and Engineering > Computer Science Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	15372
Identification Number:	https://doi.org/10.1109/CEC.2013.6557931
Depositing User:	Edgar Galvan
Date Deposited:	31 Jan 2022 16:22
Journal or Publication Title:	IEEE Transactions on Evolutionary Computation
Publisher:	IEEE
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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