Affiliations: [a] Department of Education Sciences in Early Childhood, School of Education Sciences, Democritus University of Thrace, Alexandroupolis, Greece | [b] Department of Computer Engineering & Informatics, School of Engineering, University of Patras, Patras, Greece
Correspondence:
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Corresponding author: Jim Prentzas, Department of Education Sciences in Early Childhood, School of Education Sciences, Democritus University of Thrace, 68100 Nea Chili, Alexandroupolis, Greece. Tel.: +30 25510 30086; E-mail: dprentza@psed.duth.gr.
Abstract: 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.
