Walter, Andrew, Wu, Shimeng, Tyrrell, Andy orcid.org/0000-0002-8533-2404 et al. (5 more authors) (2023) Artificial Neural Microcircuits for use in Neuromorphic System Design. In: ALife 2023: Ghost in the Machine:Proceedings. ALife 2023, 24-28 Jul 2023, University of Hokkaido. MIT Press , JPN , pp. 51-58.
Abstract
Artificial Neural Networks (ANNs) are one of the most widely employed forms of biomorphic computation. However (unlike the biological nervous systems they draw inspiration from) the current trend is for ANNs to be structurally homogeneous. Furthermore, this structural homogeneity requires the application of complex training & learning tools that produce application specific ANNs, susceptible to pitfalls like overfitting. In this paper, an alternative approach is suggested, inspired by the role played in biology by Neural Microcircuits, the so called “fundamental processing elements” of organic nervous systems. How large neural networks can be assembled using Artificial Neural Microcircuits, intended as off-the-shelf components, is articulated; before showing the results of initial work to produce a catalogue of such Microcircuits though the use of Novelty Search.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | This is an author-produced version of the published paper. Uploaded in accordance with the University’s Research Publications and Open Access policy. |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Electronic Engineering (York) |
Funding Information: | Funder Grant number EPSRC EP/W003759/1 |
Depositing User: | Pure (York) |
Date Deposited: | 23 Aug 2023 10:50 |
Last Modified: | 08 Feb 2025 00:13 |
Status: | Published |
Publisher: | MIT Press |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:202697 |
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