dc.contributor.author | Oros, N. | |
dc.contributor.author | Steuber, Volker | |
dc.contributor.author | Davey, N. | |
dc.contributor.author | Canamero, L. | |
dc.contributor.author | Adams, R.G. | |
dc.date.accessioned | 2008-10-02T14:14:08Z | |
dc.date.available | 2008-10-02T14:14:08Z | |
dc.date.issued | 2008 | |
dc.identifier.citation | Oros , N , Steuber , V , Davey , N , Canamero , L & Adams , R G 2008 , ' Adaptive Olfactory Encoding in Agents Controlled by Spiking Neural Networks ' , Lecture Notes in Computer Science (LNCS) , vol. 5040 , no. From Animals to Animats 10 , pp. 148-158 . https://doi.org/10.1007/978-3-540-69134-1_15 | |
dc.identifier.issn | 0302-9743 | |
dc.identifier.other | dspace: 2299/2422 | |
dc.identifier.other | ORCID: /0000-0003-0186-3580/work/133139215 | |
dc.identifier.uri | http://hdl.handle.net/2299/2422 | |
dc.description | “The original publication is available at www.springerlink.com”. Copyright Springer | |
dc.description.abstract | We created a neural architecture that can use two different types of information encoding strategies depending on the environment. The goal of this research was to create a simulated agent that could react to two different overlapping chemicals having varying concentrations. The neural network controls the agent by encoding its sensory information as temporal coincidences in a low concentration environment, and as firing rates at high concentration. With such an architecture, we could study synchronization of firing in a simple manner and see its effect on the agent’s behaviour. | en |
dc.format.extent | 638620 | |
dc.language.iso | eng | |
dc.relation.ispartof | Lecture Notes in Computer Science (LNCS) | |
dc.subject | neural encoding | |
dc.subject | firing rate | |
dc.subject | temporal coincidence | |
dc.title | Adaptive Olfactory Encoding in Agents Controlled by Spiking Neural Networks | en |
dc.contributor.institution | School of Computer Science | |
dc.contributor.institution | Science & Technology Research Institute | |
dc.contributor.institution | Centre for Computer Science and Informatics Research | |
dc.contributor.institution | Department of Computer Science | |
dc.contributor.institution | School of Physics, Engineering & Computer Science | |
dc.contributor.institution | Centre of Data Innovation Research | |
dc.contributor.institution | Centre for Future Societies Research | |
dc.description.status | Peer reviewed | |
rioxxterms.versionofrecord | 10.1007/978-3-540-69134-1_15 | |
rioxxterms.type | Journal Article/Review | |
herts.preservation.rarelyaccessed | true | |