An evolutionary approach to the study of non-trivial collective behavior in cellular automata

被引：0

作者：

Jiménez-Morales, F ^{[1
]}

机构：

[1] Univ Sevilla, Dept Fis Mat Condensada, E-41080 Seville, Spain

来源：

CELLULAR AUTOMATA, PROCEEDINGS | 2002年 / 2493卷

关键词：

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：

A genetic algorithm (CA) is used to evolve two and one dimensional cellular automata (CA) to perform a non-trivial collective behavior task. Using as fitness function the average area in the iterative map, the CA is able to discover several rules with the desired behavior. In d = 2 we study the scaling of the attractor versus lattice size and noise. In d = 1, using the tools of the computational mechanics, the structural organization of the CA dynamics is uncovered.

引用

页码：32 / 43

页数：12

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