Evolutionary strategy for learning multiple-valued logic functions

被引：0

作者：

Ngom, A ^{[1
]}

Simovici, DA ^{[1
]}

Stojmenovic, I ^{[1
]}

机构：

[1] Univ Windsor, Dept Comp Sci, Windsor, ON N9B 3P4, Canada

来源：

IC-AI'2001: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOLS I-III | 2001年

关键词：

multiple-valued logic; multiple-threshold perceptron; evolution strategy; neural network; partitioning method; constructive algorithm;

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 consider the problem of synthesizing multiple-valued logic functions by neural networks. An evolutionary strategy (ES) which finds the longest strip in V subset of or equal to K-n is described A strip contains points located between two parallel hyperplanes. Repeated application of ES partitions the space V into certain number of strips, each of them cot-responding to a hidden unit. We construct neural networks based on these hidden units. Preliminary experimental results are presented and discussed.

引用

页码：731 / 737

页数：7

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