Semantic analysis of program initialisation in genetic programming

Beadle, Lawrence and Johnson, Colin G. (2009) Semantic analysis of program initialisation in genetic programming. Genetic Programming and Evolvable Machines, 10 (3). pp. 307-337. ISSN 1389-2576. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

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 Abstract Population initialisation in genetic programming is both easy, because random combinations of syntax can be generated straightforwardly, and hard, because these random combinations of syntax do not always produce random and diverse program behaviours. In this paper we perform analyses of behavioural diversity, the size and shape of starting populations, the effects of purely semantic program initialisation and the importance of tree shape in the context of program initialisation. To achieve this, we create four different algorithms, in addition to using the traditional ramped half and half technique, applied to seven genetic programming problems. We present results to show that varying the choice and design of program initialisation can dramatically influence the performance of genetic programming. In particular, program behaviour and evolvable tree shape can have dramatic effects on the performance of genetic programming. The four algorithms we present have different rates of success on different problems.

Item Type: Article
Uncontrolled keywords: Genetic programming, Program initialisation, Program semantics, Program structure
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 12:16
Last Modified: 17 Jul 2012 14:34
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