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
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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: | 06 Dec 2023 09:54 |
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: | https://doi.org/10.1007/978-3-642-33269-2_7 |
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