Registro completo de metadatos
| Campo DC | Valor | Lengua/Idioma |
|---|---|---|
| dc.creator | Gutnisky, D. A. | - |
| dc.creator | Zelmann, R. | - |
| dc.creator | Zanutto, Bonifacio Silvano | - |
| dc.date | 2017-06-21T15:41:58Z | - |
| dc.date | 2017-06-21T15:41:58Z | - |
| dc.date | 2006-12 | - |
| dc.date | 2017-05-16T20:33:16Z | - |
| dc.date.accessioned | 2019-04-29T15:31:17Z | - |
| dc.date.available | 2019-04-29T15:31:17Z | - |
| dc.date.issued | 2006-12 | - |
| dc.identifier | Gutnisky, D. A.; Zelmann, R.; Zanutto, Bonifacio Silvano; Multiagent team formation performed by operant learning: an animat approach; Institute Of Electrical And Electronics Engineers; Proceedings of International Joint Conference on Neural Networks; 2006; 12-2006; 2944-2950 | - |
| dc.identifier | 2161-4393 | - |
| dc.identifier | http://hdl.handle.net/11336/18532 | - |
| dc.identifier | 2161-4407 | - |
| dc.identifier | CONICET Digital | - |
| dc.identifier | CONICET | - |
| dc.identifier.uri | http://rodna.bn.gov.ar:8080/jspui/handle/bnmm/295661 | - |
| dc.description | An animat approach to dynamic team formation in a group of distributed robots is studied. The goal is that robots learn to align with the others in order to form a row or a column without having communication among them, just local sensing and a reinforcement signal. The action of the robot is controlled by a biologically plausible neural network model of operant learning. The remarkable performance achieved by the proposed model allows the building of new artificial intelligence agents based on neurobiology, psychology and ethology research. | - |
| dc.description | Fil: Gutnisky, D. A.. | - |
| dc.description | Fil: Zelmann, R.. | - |
| dc.description | Fil: Zanutto, Bonifacio Silvano. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; Argentina | - |
| dc.format | application/pdf | - |
| dc.format | application/pdf | - |
| dc.language | eng | - |
| dc.publisher | Institute Of Electrical And Electronics Engineers | - |
| dc.relation | info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/ 10.1109/IJCNN.2006.247228 | - |
| dc.relation | info:eu-repo/semantics/altIdentifier/url/http://ieeexplore.ieee.org/document/1716498/ | - |
| dc.rights | info:eu-repo/semantics/restrictedAccess | - |
| dc.rights | https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ | - |
| dc.source | reponame:CONICET Digital (CONICET) | - |
| dc.source | instname:Consejo Nacional de Investigaciones Científicas y Técnicas | - |
| dc.source | instacron:CONICET | - |
| dc.subject | OPERANT BEHAVIOR | - |
| dc.subject | MULTIAGENT SYSTEM | - |
| dc.subject | NEURAL NETWORKS | - |
| dc.subject | REINFORCEMENT LEARNING | - |
| dc.subject | Neurociencias | - |
| dc.subject | Medicina Básica | - |
| dc.subject | CIENCIAS MÉDICAS Y DE LA SALUD | - |
| dc.subject | Control Automático y Robótica | - |
| dc.subject | Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información | - |
| dc.subject | INGENIERÍAS Y TECNOLOGÍAS | - |
| dc.title | Multiagent team formation performed by operant learning: an animat approach | - |
| dc.type | info:eu-repo/semantics/article | - |
| dc.type | info:eu-repo/semantics/publishedVersion | - |
| dc.type | info:ar-repo/semantics/articulo | - |
| Aparece en las colecciones: | CONICET | |
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