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 | |||||||||
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Divisions : | Faculty of Engineering and Physical Sciences > Computing Science | |||||||||
Authors : |
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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 : | 31 Oct 2017 13:58 | |||||||||
URI: | http://epubs.surrey.ac.uk/id/eprint/504 |
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