Burles, Nathan John orcid.org/0000-0003-3030-1675, Austin, Jim orcid.org/0000-0001-5762-8614 and O'Keefe, Simon orcid.org/0000-0001-5957-2474 (2013) Extending the Associative Rule Chaining Architecture for Multiple Arity Rules. In: Proceedings of the Ninth International Workshop on Neural-Symbolic Learning and Reasoning. Ninth International Workshop on Neural-Symbolic Learning and Reasoning, 05 Aug 2013 , CHN , pp. 47-51.
Abstract
The Associative Rule Chaining Architecture uses distributed associative memories and superimposed distributed representations in order to perform rule chaining efficiently [Austin et al., 2012]. Previous work has focused on rules with only a single antecedent, in this work we extend the architecture to work with multiple-arity rules and show that it continues to operate effectively.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 09 Apr 2014 17:00 |
Last Modified: | 04 Jan 2025 00:25 |
Status: | Published |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:75692 |
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Filename: extendingARCAForMultipleArityRules.pdf
Description: extendingARCAForMultipleArityRules