Evolving high capacity associative memories with efficient wiring

被引:0
|
作者
Adams, R [1 ]
Calcraft, L [1 ]
Davey, N [1 ]
机构
[1] Univ Hertfordshire, Sch Comp Sci, Hatfield AL10 9AB, Herts, England
关键词
associative memory; neural network; genetic algorithm; small world network; connectivity;
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
We investigate sparse networks of threshold units, trained with the perceptron learning rule to act as associative memories. The units have position and are placed in a ring so that the wiring cost is a meaningful measure. A Genetic Algorithm is used to evolve networks that have efficient wiring, but also good functionality. It is shown that this is possible, and that the connection strategy used by the networks appears to maintain connectivity at all distances, but with the probability of a connection decreasing linearly with distance.
引用
收藏
页码:3168 / 3173
页数:6
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