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dc.contributor.authorChristodoulou, Chris C.en
dc.contributor.authorCleanthous, A.en
dc.creatorChristodoulou, Chris C.en
dc.creatorCleanthous, A.en
dc.date.accessioned2019-11-13T10:39:16Z
dc.date.available2019-11-13T10:39:16Z
dc.date.issued2011
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/53712
dc.description.abstractIn this note, we demonstrate that the high firing irregularity produced by the leaky integrate-and-fire neuron with the partial somatic reset mechanism, which has been shown to be the most likely candidate to reflect the mechanism used in the brain for reproducing the highly irregular cortical neuron firing at high rates (Bugmann, Christodoulou, & Taylor, 1997en
dc.description.abstractChristodoulou & Bugmann, 2001), enhances learning. More specifically, it enhances reward-modulated spike-timing-dependent plasticity with eligibility trace when used in spiking neural networks, as shown by the results when tested in the simple benchmark problem of XOR, as well as in a complex multiagent setting task. © 2011 Massachusetts Institute of Technology.en
dc.sourceNeural computationen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-79951568245&doi=10.1162%2fNECO_a_00090&partnerID=40&md5=6f26d931706e2b2d3add844ca6d04683
dc.subjectlearningen
dc.subjectphysiologyen
dc.subjectNeuronsen
dc.subjectartificial neural networken
dc.subjectNeural Networks (Computer)en
dc.subjectnerve cellen
dc.subjectAction Potentialsen
dc.subjectgameen
dc.subjectaction potentialen
dc.subjectGames, Experimentalen
dc.titleDoes high firing irregularity enhance learning?en
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.1162/NECO_a_00090
dc.description.volume23
dc.description.issue3
dc.description.startingpage656
dc.description.endingpage663
dc.author.faculty002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Πληροφορικής / Department of Computer Science
dc.type.uhtypeArticleen
dc.description.notes<p>Cited By :6</p>en
dc.source.abbreviationNeural Comp.en
dc.contributor.orcidChristodoulou, Chris C. [0000-0001-9398-5256]
dc.gnosis.orcid0000-0001-9398-5256


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