Towards a framework for the analysis of regulative norm performance in complex networks

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To access the full text documents, please follow this link: http://hdl.handle.net/2117/22835

dc.contributor	Universitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics
dc.contributor	Universitat Politècnica de Catalunya. KEMLG - Grup d'Enginyeria del Coneixement i Aprenentatge Automàtic
dc.contributor.author	Oliva Felipe, Luis Javier
dc.contributor.author	Álvarez Napagao, Sergio
dc.contributor.author	Vázquez Salceda, Javier
dc.date	2012
dc.identifier.citation	Oliva, L.; Alvarez-Napagao, Sergio; Vazquez, J. Towards a framework for the analysis of regulative norm performance in complex networks. A: Agreement Technologies. "Proceedings of the First International Conference on Agreement Technologies (AT 2012)". Dubrovnik: 2012, p. 103-104.
dc.identifier.citation	1613-0073
dc.identifier.uri	http://hdl.handle.net/2117/22835
dc.language.iso	eng
dc.relation	http://ceur-ws.org/Vol-918/111110103.pdf
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors
dc.subject	Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
dc.subject	provenance
dc.subject	normative systems
dc.subject	complex networks
dc.subject	monitoring
dc.title	Towards a framework for the analysis of regulative norm performance in complex networks
dc.type	info:eu-repo/semantics/submittedVersion
dc.type	info:eu-repo/semantics/conferenceObject
dc.description.abstract	Systemic analysis of dynamics in complex networks has allured interest from different fields. Norms are a mechanism that can be useful to govern or guide the behavior of agents in such scenarios. Such effects of norms can be analyzed in different terms, such as emergence, spread, equilibrium oscillations and stability. In this paper, we present an analysis of the life-cycle of deontic norms in scale-free networks, with special focus on the long-term effects of different agents’ personalities and their structural properties. Our approach combines provenance-aware monitoring traces and the analysis of the dynamics emerged in the relations between agents by means of complex network representations.
dc.description.abstract	Peer Reviewed

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