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dc.contributor.authorCapdepuy, P.
dc.contributor.authorPolani, D.
dc.contributor.authorNehaniv, C.L.
dc.date.accessioned2011-10-18T14:01:14Z
dc.date.available2011-10-18T14:01:14Z
dc.date.issued2007
dc.identifier.citationCapdepuy , P , Polani , D & Nehaniv , C L 2007 , Maximization of Potential Information Flow as a Universal Utility for Collective Behaviour . in Procs of the 2007 IEEE Symposium on Artificial Life (CI-ALife 2007) . Institute of Electrical and Electronics Engineers (IEEE) , pp. 207-213 .
dc.identifier.otherPURE: 422192
dc.identifier.otherPURE UUID: c52bd79b-969a-4a3d-aff9-fb2a8b2d37cb
dc.identifier.otherdspace: 2299/1736
dc.identifier.otherScopus: 34548797964
dc.identifier.otherORCID: /0000-0002-3233-5847/work/86098119
dc.identifier.urihttp://hdl.handle.net/2299/6712
dc.description.abstractWe explore how information theoretic quantities such as potential information flow (empowerment) can be used as a drive toward complex collective behaviour in the context of multi-agent systems. In a first experiment, we investigate the empowerment of two agents interacting in a grid world. We show that some conditions lead to higher empowerment than others, depending on the amount of interaction and the amount of information shared by the agents. We then investigate more deeply the tradeoff between freedom of the agents and the constraints they impose on each other. We show that there exist a trade-off between these where empowerment is maximized. In a third experiment, we show that agents behaving so as to maximize potential information transfer over time generate a wide range of complex collective behaviours. We then discuss how these notions can be compared to what happens in natural systems.en
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartofProcs of the 2007 IEEE Symposium on Artificial Life (CI-ALife 2007)
dc.titleMaximization of Potential Information Flow as a Universal Utility for Collective Behaviouren
dc.contributor.institutionSchool of Computer Science
dc.contributor.institutionScience & Technology Research Institute
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.contributor.institutionAdaptive Systems
dc.contributor.institutionDepartment of Computer Science
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.contributor.institutionCentre for Future Societies Research
rioxxterms.versionVoR
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue


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