Multi-Level Neutrality in Optimization

Johnson, Colin G. (2008) Multi-Level Neutrality in Optimization. In: Proceedings of the 2008 IEEE World Congress on Computational Intelligence, Jun 01-06, 2008, Hong Kong, Peoples R China.

PDF
Download (293Kb)	Preview

Abstract

This paper explores the idea of neutrality in heuristic optimization algorithms. In particular, the effect of having multiple levels of neutrality in representations is explored. Two experiments using a fitness-adaptive walk algorithm are carried out: the first is concerned with function optimization with Random Boolean Networks, the second with a tunable neutral mapping applied to the hierarchical if-and-only-if function. In both of these cases it is shown that a two-level neutral mapping can be found that performs better than both nonneutral mappings and mappings with a single level of neutrality.

Item Type:	Conference or workshop item (Paper)
Uncontrolled keywords:	Genetic Algorithms; Neutrality; Hill-Climbing; Optimization
Subjects:	Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions:	Faculties > Science Technology and Medical Studies > School of Computing > Applied and Interdisciplinary Informatics Group
Depositing User:	Mark Wheadon
Date Deposited:	29 Mar 2010 12:10
Last Modified:	06 Sep 2011 04:52
Resource URI:	http://kar.kent.ac.uk/id/eprint/24007 (The current URI for this page, for reference purposes)

• Depositors only (login required):