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

被引:0
|
作者
Sarafopoulos, Anargyros [1 ]
Buxton, Bernard [2 ]
机构
[1] Bournemouth Univ, Natl Ctr Comp Animat, Poole BH12 5BB, Dorset, England
[2] UCL, Dept Comp Sci, London WC1E 6BT, England
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中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
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页码:68 / +
页数:2
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