Modelling the extrapolation ability of multi-layer pereeptrons

被引:0
|
作者
Browne, A [1 ]
机构
[1] London Guildhall Univ, Sch Comp Informat Syst & Math, London EC3N 1JY, England
关键词
neural networks; extrapolation; distributed representation; localist representation; identity task; circular convolution;
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
To give a good explanation of human cognition and perform certain practical tasks connectionist systems must be able to extrapolate. This paper explores the relationship between the input representation used for a task and the extrapolation performance of an MLP trained on that task. It has been discovered that representation has a marked effect on the extrapolation properties of MLPs when trained to do the identity task.
引用
收藏
页码:429 / 433
页数:5
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