dc.contributor.author | Christodoulou, Chris C. | en |
dc.contributor.author | Cleanthous, A. | en |
dc.creator | Christodoulou, Chris C. | en |
dc.creator | Cleanthous, A. | en |
dc.date.accessioned | 2019-11-13T10:39:16Z | |
dc.date.available | 2019-11-13T10:39:16Z | |
dc.date.issued | 2011 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/53712 | |
dc.description.abstract | In 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, 1997 | en |
dc.description.abstract | Christodoulou & 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.source | Neural computation | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-79951568245&doi=10.1162%2fNECO_a_00090&partnerID=40&md5=6f26d931706e2b2d3add844ca6d04683 | |
dc.subject | learning | en |
dc.subject | physiology | en |
dc.subject | Neurons | en |
dc.subject | artificial neural network | en |
dc.subject | Neural Networks (Computer) | en |
dc.subject | nerve cell | en |
dc.subject | Action Potentials | en |
dc.subject | game | en |
dc.subject | action potential | en |
dc.subject | Games, Experimental | en |
dc.title | Does high firing irregularity enhance learning? | en |
dc.type | info:eu-repo/semantics/article | |
dc.identifier.doi | 10.1162/NECO_a_00090 | |
dc.description.volume | 23 | |
dc.description.issue | 3 | |
dc.description.startingpage | 656 | |
dc.description.endingpage | 663 | |
dc.author.faculty | 002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences | |
dc.author.department | Τμήμα Πληροφορικής / Department of Computer Science | |
dc.type.uhtype | Article | en |
dc.description.notes | <p>Cited By :6</p> | en |
dc.source.abbreviation | Neural Comp. | en |
dc.contributor.orcid | Christodoulou, Chris C. [0000-0001-9398-5256] | |
dc.gnosis.orcid | 0000-0001-9398-5256 | |