Neural network models for abduction problems solving

被引：0

作者：

Ariton, Viorel ^{[1
]}

Ariton, Doinita ^{[2
]}

机构：

[1] Danubius Univ, Lunca Siretului 3, Galati, Romania

[2] Dunarea Jos Univ, Galati 800001, Romania

来源：

KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS: KES 2007 - WIRN 2007, PT I, PROCEEDINGS | 2007年 / 4692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：

Due to its' connectionist nature, abductive reasoning may get neural network implementations that yet require structure adaptation to the abduction problems which Bylander and the team asserted. The paper proposes neural models for all known abduction problems, in a really unified manner, and with a sound and straightforward embedding in the existing neural network paradigms.

引用

页码：52 / +

页数：2

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