Neurules and connectionist expert systems: Unexplored neuro-symbolic reasoning aspects

被引:1
|
作者
Prentzas, Jim [1 ]
Hatzilygeroudis, Ioannis [2 ]
机构
[1] Democritus Univ Thrace, Sch Educ Sci, Dept Educ Sci Early Childhood, Nea Chili 68100, Alexandroupolis, Greece
[2] Univ Patras, Sch Engn, Dept Comp Engn & Informat, Patras, Greece
来源
INTELLIGENT DECISION TECHNOLOGIES-NETHERLANDS | 2021年 / 15卷 / 04期
关键词
Combinations of intelligent methods; hybrid intelligent systems; neuro-symbolic approaches; reasoning; hybrid expert systems; explainable Artificial Intelligence; GENETIC ALGORITHM; FUZZY SYSTEM; NETWORK; OPTIMIZATION;
D O I
10.3233/IDT-210211
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Neuro-symbolic approaches combine neural and symbolic methods. This paper explores aspects regarding the reasoning mechanisms of two neuro-symbolic approaches, that is, neurules and connectionist expert systems. Both provide reasoning and explanation facilities. Neurules are a type of neuro-symbolic rules tightly integrating the neural and symbolic components, giving pre-eminence to the symbolic component. Connectionist expert systems give pre-eminence to the connectionist component. This paper explores reasoning aspects about neurules and connectionist expert systems that have not been previously addressed. As far as neurules are concerned, an aspect playing a role in conflict resolution (i.e., order of neurules) is explored. Experimental results show an improvement in reasoning efficiency. As far as connectionist expert systems are concerned, variations of the reasoning mechanism are explored. Experimental results are presented for them as well showing that one of the variations generally performs better than the others.
引用
收藏
页码:761 / 777
页数:17
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