Connectionist inference models

The performance of symbolic inference tasks has long been a challenge to connectionists. In this paper, we present an extended survey of this area. Existing connectionist inference systems are reviewed, with particular reference to how they perform variable binding and rule-based reasoning and wheth...

Full description

Saved in:
Bibliographic Details
Published in:Neural networks 2001-12, Vol.14 (10), p.1331-1355
Main Authors: Browne, Antony, Sun, Ron
Format: Article
Language:English
Subjects:
Animals
Applied sciences
Artificial intelligence
Computer science
control theory
systems
Connectionism. Neural networks
Distributed representations
Exact sciences and technology
Fuzzy Logic
Humans
Localist representations
Neural Networks (Computer)
Resolution
Symbolic inference
Variable binding
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The performance of symbolic inference tasks has long been a challenge to connectionists. In this paper, we present an extended survey of this area. Existing connectionist inference systems are reviewed, with particular reference to how they perform variable binding and rule-based reasoning and whether they involve distributed or localist representations. The benefits and disadvantages of different representations and systems are outlined, and conclusions drawn regarding the capabilities of connectionist inference systems when compared with symbolic inference systems or when used for cognitive modelling.
ISSN:0893-6080
1879-2782
DOI:10.1016/S0893-6080(01)00109-5