A neural cognitive architecture
Huyck, Christian R. ORCID: https://orcid.org/0000-0003-4015-3549
(2020)
A neural cognitive architecture.
Cognitive Systems Research, 59
.
pp. 171-178.
ISSN 1389-0417
[Article]
(doi:10.1016/j.cogsys.2019.09.023)
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Abstract
It is difficult to study the mind, but cognitive architectures are one tool. As the mind emerges from the behaviour of the brain, neuropsychological methods are another method to study the mind, though a rather indirect method. A cognitive architecture that is implemented in spiking neurons is a method of studying the mind that can use neuropsychological evidence directly. A neural cognitive architecture, based on rule based systems and associative memory, can be readily implemented, and would provide a good bridge between standard cognitive architectures, such as \Soar, and neuropsychology. This architecture could be implemented in spiking neurons, and made available via the Human Brain Project, which provides a good collaborative environment. The architecture could be readily extended to use spiking neurons for subsystems, such as spatial reasoning, and could evolve over time toward a complete architecture. The theory behind this architecture could evolve over time. Simplifying assumptions, made explicit, such as those behind the rule based system, could gradually be replaced by more neuropsychologically accurate behaviour. The overall task of collaborative architecture development would be eased by direct evidence of the actual neural cognitive architectures in human brains. While the initial architecture is biologically inspired, the ultimate goal is a biological cognitive architecture.
Item Type: | Article |
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Research Areas: | A. > School of Science and Technology > Computer Science > Artificial Intelligence group |
Item ID: | 27593 |
Notes on copyright: | © 2019. This author's accepted manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ |
Useful Links: | |
Depositing User: | Chris Huyck |
Date Deposited: | 19 Sep 2019 20:11 |
Last Modified: | 07 Jun 2022 20:46 |
URI: | https://eprints.mdx.ac.uk/id/eprint/27593 |
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