Using a genetic algorithm to evolve cellular automata for 2D/3D computational development

被引：0

作者：

Chavoya, Arturo ^{[1
]}

Duthen, Yves ^{[1
]}

机构：

[1] Univ Toulouse 1, Image Synth & Virtual Real Team, 1 Pl Anatole France, F-31042 Toulouse, France

来源：

GECCO 2006: GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, VOL 1 AND 2 | 2006年

关键词：

genetic algorithms; cellular automata; computational development;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Form generation or morphogenesis is one of the main stages of both artificial and natural development. This paper provides results from experiments in which a genetic algorithm (CA) was used to evolve cellular automata (CA) to produce predefined 2D and 3D shapes. The CA worked by evolving the CA rule table and the number of iterations that the model was to run. After the final chromosomes were obtained for all shapes, the CA model was allowed to run starting with a single cell in the middle of the lattice until the allowed number of iterations was reached and a shape was formed. In all cases, mean fitness values of evolved chromosomes were above 80%.

引用

页码：231 / +

页数：2

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