Conflict resolution and learning probability matching in a neural cell-assembly architecture

Article


Belavkin, R. and Huyck, C. 2011. Conflict resolution and learning probability matching in a neural cell-assembly architecture. Cognitive Systems Research. 12 (2), pp. 93-101. https://doi.org/10.1016/j.cogsys.2010.08.003
TypeArticle
TitleConflict resolution and learning probability matching in a neural cell-assembly architecture
AuthorsBelavkin, R. and Huyck, C.
Abstract

Donald Hebb proposed a hypothesis that specialised groups of neurons, called cell-assemblies (CAs), form the basis for neural encoding of symbols in the human mind. It is not clear, however, how CAs can be re-used and combined to form new representations as in classical symbolic systems. We demonstrate that Hebbian learning of synaptic weights alone is not adequate for all tasks, and that additional meta-control processes should be involved. We describe an earlier proposed architecture implementing an adaptive conflict resolution process between CAs, and then evaluate it by modelling the probability matching phenomenon in a classic two-choice task. The model and its results are discussed in view of mathematical theory of learning and existing cognitive architectures.

KeywordsArtificial intelligence; Cognitive science; Neuroscience; Decision making; Intelligent agents; Learning; Bayesian modelling; Computational neuroscience; Human experimentation
Research GroupArtificial Intelligence group
PublisherElsevier
JournalCognitive Systems Research
ISSN1389-0417
Publication dates
Print30 Jun 2011
Online26 Aug 2010
Publication process dates
Deposited27 Jan 2011
Output statusPublished
Accepted author manuscript
License
Copyright Statement

Post refereed version as permitted by publisher.
© 2010. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/

Digital Object Identifier (DOI)https://doi.org/10.1016/j.cogsys.2010.08.003
Scopus EID2-s2.0-79952196078
Web of Science identifierWOS:000288008100003
LanguageEnglish
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Belavkin, R. 2005. Entropy and information in models of learning behaviour. AISB Quarterly. 119, pp. 5-5.
Towards a theory of decision-making with paradoxes.
Belavkin, R. 2006. Towards a theory of decision-making with paradoxes. Proceedings of the Seventh International Conference on Cognitive Modelling. Trieste, Italy 2006 pp. 38-43
The duality of utility and information in optimally learning systems
Belavkin, R. 2008. The duality of utility and information in optimally learning systems. 7th IEEE International Conference on Cybernetic Intelligent Systems. London, UK 09 - 10 Sep 2008 London IEEE. https://doi.org/10.1109/UKRICIS.2008.4798960
Do neural models scale up to a human brain?
Belavkin, R. 2007. Do neural models scale up to a human brain? International Joint Conference on Neural Networks (IJCNN 2007). Orlando, Florida 12 - 17 Aug 2007 IEEE. pp. 2312-2317 https://doi.org/10.1109/IJCNN.2007.4371319
Creating hierarchical categories using cell assemblies
Huyck, C. 2007. Creating hierarchical categories using cell assemblies. Connection Science. 19 (1), pp. 1-24. https://doi.org/10.1080/09540090600779713
Relevance feedback and cross-language information retrieval
Orengo, V. and Huyck, C. 2006. Relevance feedback and cross-language information retrieval. Information Processing and Management. 42 (5), pp. 1203-1217. https://doi.org/10.1016/j.ipm.2005.12.003
Information retrieval and categorisation using a cell assembly network
Huyck, C. and Orengo, V. 2005. Information retrieval and categorisation using a cell assembly network. Neural Computing and Applications. 14 (4), pp. 282-289. https://doi.org/10.1007/s00521-004-0464-6
Acting irrationally to improve performance in stochastic worlds
Belavkin, R. 2005. Acting irrationally to improve performance in stochastic worlds. Bramer, M., Coenen, F. and Allen, T. (ed.) 25th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence. Cambridge, UK 2005 Springer. pp. 305-316 https://doi.org/10.1007/978-1-84628-226-3_23
Overlapping cell assemblies from correlators
Huyck, C. 2004. Overlapping cell assemblies from correlators. Neural Computing Letters. 56, pp. 435-439. https://doi.org/10.1016/j.neucom.2003.08.003