Poli, Riccardo and Galván-López, Edgar (2007) On the Effects of Bit-Wise Neutrality on Fitness Distance Correlation, Phenotypic Mutation Rates and Problem Hardness. Lecture Notes in Computer Science, 4436. pp. 138-164. ISSN 0302-9743

Preview

Download (885kB) | Preview

Abstract

Kimura’s neutral theory of evolution has inspired researchers from the evolutionary computation community to incorporate neutrality into Evolutionary Algorithms (EAs) in the hope that it can aid evolution. The effects of neutrality on evolutionary search have been considered in a number of studies, the results of which, however, have been highly contradictory. In this paper, we analyse the reasons for this and we make an effort to shed some light on neutrality by addressing them. We consider two very simple forms of neutrality: constant neutrality — a neutral network of constant fitness, identically distributed in the whole search space — and bit-wise neutrality, where each phenotypic bit is obtained by transforming a group of genotypic bits via an encoding function. We study these forms of neutrality both theoretically and empirically (both for standard benchmark functions and a class of random MAX-SAT problems) to see how and why they influence the behaviour and performance of a mutation-based EA. In particular, we analyse how the fitness distance correlation of landscapes changes under the effect of different neutral encodings and how phenotypic mutation rates vary as a function of genotypic mutation rates. Both help explain why the behaviour of a mutation-based EA may change so radically as problem, form of neutrality and mutation rate are varied.

Item Type:	Article
Keywords:	Neutrality; Phenotypic Mutation Rates; Problem Hardness; Fitness Distance Correlation; MAX-SAT; Genotype-Phenotype Mappings;
Academic Unit:	Faculty of Science and Engineering > Computer Science Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	15434
Identification Number:	https://doi.org/10.1007/978-3-540-73482-6_9
Depositing User:	Edgar Galvan
Date Deposited:	08 Feb 2022 12:44
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