On the Design of Neuro-controllers for Individual and Social Learning Behaviour in Autonomous Robots: An Evolutionary Approach

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dc.contributor.author Pini, Giovanni
dc.contributor.author Tuci, Elio
dc.date.accessioned 2010-09-07T16:20:35Z
dc.date.available 2010-09-07T16:20:35Z
dc.date.issued 2008-03-01
dc.identifier.citation Pini , G & Tuci , E 2008 , ' On the Design of Neuro-controllers for Individual and Social Learning Behaviour in Autonomous Robots: An Evolutionary Approach ' Connection Science , vol 20 , no. 2-3 , pp. 211-230 . en
dc.identifier.issn 0954-0091
dc.identifier.other PURE: 150563
dc.identifier.other dspace: 2160/5403
dc.identifier.uri http://hdl.handle.net/2160/5403
dc.identifier.uri http://www.informaworld.com/smpp/970056912-5665362/content~db=all~content=a793279370~frm=titlelink en
dc.description Pini G., Tuci E. On the Design of Neuro-controllers for Individual and Social Learning Behaviour in Autonomous Robots: An Evolutionary Approach. Connection Science Journal, Vol. 20, No 2-3, pp 211-230, 2008. Special Issue: Social Learning in Embodied Agents en
dc.description.abstract In biology/psychology, the capability of natural organisms to learn from the observation/interaction with conspecifics is referred to as social learning. Roboticists have recently developed an interest in social learning, since it might represent an effective strategy to enhance the adaptivity of a team of autonomous robots. In this study, we show that a methodological approach based on artifcial neural networks shaped by evolutionary computation techniques can be successfully employed to synthesise the individual and social learning mechanisms for robots required to learn a desired action (i.e. phototaxis or antiphototaxis). en
dc.format.extent 20 en
dc.language.iso eng
dc.relation.ispartof Connection Science en
dc.subject social learning en
dc.subject evolutionary robotics en
dc.subject autonomous robots en
dc.subject artificial neural networks en
dc.title On the Design of Neuro-controllers for Individual and Social Learning Behaviour in Autonomous Robots: An Evolutionary Approach en
dc.type Text en
dc.type.publicationtype Special issue (Journal) en
dc.identifier.doi http://dx.doi.org/10.1080/09540090802092014
dc.contributor.institution Department of Computer Science en
dc.contributor.institution Intelligent Robotics Group en
dc.description.status Peer reviewed en


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