Empirical comparison of evolutionary representations of the inverse problem for iterated function systems

Authors:
Anargyros Sarafopoulos;Bernard Buxton
Affiliations:
National Centre for Computer Animation, Bournemouth University, Poole, Dorset, UK;Department of Computer Science, University College London, London, UK
Venue:
EuroGP'07 Proceedings of the 10th European conference on Genetic programming
Year:
2007

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Abstract

In this paper we present an empirical comparison between evolutionary representations for the resolution of the inverse problem for iterated function systems (IFS). We introduce a class of problem instances that can be used for the comparison of the inverse IFS problem as well as a novel technique that aids exploratory analysis of experiment data. Our comparison suggests that representations that exploit problem specific information, apart from quality/fitness feedback, perform better for the resolution of the inverse problem for IFS.