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Variable Discrimination of Crossover Versus Mutation Using Parameterized Modular Structure

Mills, Rob and Watson, Richard A., Thierens, Dirk and Lipson, Hod(eds.) (2007) Variable Discrimination of Crossover Versus Mutation Using Parameterized Modular Structure Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2007), pp. 1312-1319.

Record type: Article

Abstract

Recent work has provided functions that can be used to prove a principled distinction between the capabilities of mutation-based and crossover-based algorithms. However, prior functions are isolated problem instances that do not provide much intuition about the space of possible functions that is relevant to this distinction or the characteristics of the problem class that affect the relative success of these operators. Modularity is a ubiquitous and intuitive concept in design, engineering and optimisation, and can be used to produce functions that discriminate the ability of crossover from mutation. In this paper, we present a new approach to representing modular problems, which parameterizes the amount of modular structure that is present in the epistatic dependencies of the problem. This adjustable level of modularity can be used to give rise to tuneable discrimination of the ability of genetic algorithms with crossover versus mutation-only algorithms.

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Published date: July 2007
Organisations: Agents, Interactions & Complexity, EEE

Identifiers

Local EPrints ID: 264033
URI: http://eprints.soton.ac.uk/id/eprint/264033
PURE UUID: ec820a0c-5e8b-4ab0-ac77-9c41f1492218

Catalogue record

Date deposited: 23 May 2007
Last modified: 18 Jul 2017 07:40

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Contributors

Author: Rob Mills
Editor: Dirk Thierens
Editor: Hod Lipson

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