Tread: a new genetic programming representation aimed at research of long term complexity growth

Lewis, T.E. and Magoulas, George D. (2008) Tread: a new genetic programming representation aimed at research of long term complexity growth. In: UNSPECIFIED (ed.) Proceedings of the 10th annual conference on genetic and evolutionary computation. New York, USA: Association for Computing Machinery, pp. 1339-1340. ISBN 9781605581309.

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Official URL: http://dx.doi.org/10.1145/1389095.1389353

Abstract

Several forms of computer program (or representation) have been proposed for Genetic Programming (GP) systems to evolve, such as linear, tree based or graph based. Typically, GP representations are highly effective during the initial search phases of evolution but stagnate before deep levels of complexity are acquired. A new representation, TREAD, is proposed to combine aspects of flow of execution and flow of data systems. The distinguishing features of TREAD are designed for researching improvements to the long term acquisition of novel features in GP (at the expense of the speed of the initial search if necessary). TREAD is validated on a symbolic regression problem and is found to be capable of successfully developing solutions through artificial evolution.

Metadata

Item Type:	Book Section
School:	Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
Research Centres and Institutes:	Birkbeck Knowledge Lab
Depositing User:	Sarah Hall
Date Deposited:	19 Jul 2013 11:10
Last Modified:	09 Aug 2023 12:33
URI:	https://eprints.bbk.ac.uk/id/eprint/7741

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