Emergence of rules in cell assemblies of fLIF neurons.

Conference paper

Belavkin, R. and Huyck, C. 2008. Emergence of rules in cell assemblies of fLIF neurons. The 18th European Conference on Artificial Intelligence. University of Patras, Greece 21 - 25 Jul 2008
TypeConference paper
TitleEmergence of rules in cell assemblies of fLIF neurons.
AuthorsBelavkin, R. and Huyck, C.
Abstract

Inspired by biological cognition, CABOT project explores
the ways symbolic processing can emerge in a system of neural cell assemblies (CAs). Here we show how a stochastic meta–control process can regulate learning of associations between the CAs, the neural basis of symbols. An experiment illustrates the learning between CAs representing conditions actions pairs, which leads to CA–based representations of ‘if–then’ rules.

Research GroupArtificial Intelligence group
ConferenceThe 18th European Conference on Artificial Intelligence
Publication process dates
Deposited24 Mar 2010
Output statusPublished
Web address (URL)http://www.cwa.mdx.ac.uk/CABot/papers/ecai08/rvb-crh-ecai08-2p.pdf
LanguageEnglish
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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