Austin, Jim orcid.org/0000-0001-5762-8614, Hobson, Stephen John, Burles, Nathan John orcid.org/0000-0003-3030-1675 et al. (1 more author) (2012) A Rule Chaining Architecture Using a Correlation Matrix Memory. In: Artificial Neural Networks and Machine Learning – ICANN 2012. Lecture Notes in Computer Science . Springer , CHE , pp. 49-56.
Abstract
This paper describes an architecture based on superimposed distributed representations and distributed associative memories which is capable of performing rule chaining. The use of a distributed representation allows the system to utilise memory efficiently, and the use of superposition reduces the time complexity of a tree search to O(d), where d is the depth of the tree. Our experimental results show that the architecture is capable of rule chaining effectively, but that further investigation is needed to address capacity considerations.
Metadata
Item Type: | Book Section |
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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: | 27 May 2016 09:37 |
Last Modified: | 08 Jan 2025 00:15 |
Published Version: | https://doi.org/10.1007/978-3-642-33269-2_7 |
Status: | Published |
Publisher: | Springer |
Series Name: | Lecture Notes in Computer Science |
Refereed: | Yes |
Identification Number: | 10.1007/978-3-642-33269-2_7 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:88231 |