Connectionist inference models

Browne, Antony and Sun, Ron (2001) Connectionist inference models Neural Networks, 14. pp. 1331-1355.

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Abstract

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.

Item Type:	Article
Divisions :	Faculty of Engineering and Physical Sciences > Computing Science
Authors :	Authors Email ORCID Browne, Antony a.browne@surrey.ac.uk UNSPECIFIED Sun, Ron UNSPECIFIED UNSPECIFIED
Date :	1 January 2001
Uncontrolled Keywords :	Symbolic inference, Resolution, Variable binding, Localist representations, Distributed representations
Additional Information :	This is a pre-print version of the article. The citation for the final version is:Browne, A., & Sun, R. (2001). Connectionist inference models. Neural Networks, 14, 1331-1355. © 2001 Elsevier Science Ltd. All rights reserved. Click here to access the published version.
Depositing User :	Mr Adam Field
Date Deposited :	27 May 2010 14:09
Last Modified :	23 Sep 2013 18:28
URI:	http://epubs.surrey.ac.uk/id/eprint/504

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