2010
DOI: 10.3233/aic-2010-0479
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Robust coordination in large convention spaces

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Cited by 28 publications
(7 citation statements)
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“…The case of multiple compatible actions has been considered in stochastic coordination games, having multiple and differently valued Nash equilibria [15,16,56]. Suboptimal norms have also been considered in the context of language learning in which the compatibility of words and concepts in a lexicon enables norms to be "ranked" in terms of effectiveness [45]. However, this previous work does not consider the different types and roles of agents, or the impact of the community structure of the underlying topology.…”
Section: Related Workmentioning
confidence: 99%
“…The case of multiple compatible actions has been considered in stochastic coordination games, having multiple and differently valued Nash equilibria [15,16,56]. Suboptimal norms have also been considered in the context of language learning in which the compatibility of words and concepts in a lexicon enables norms to be "ranked" in terms of effectiveness [45]. However, this previous work does not consider the different types and roles of agents, or the impact of the community structure of the underlying topology.…”
Section: Related Workmentioning
confidence: 99%
“…The social metaphor (such as the one here described but without forgetting the related body of work in market‐based multi‐agent systems (Vytelingum et al , 2010) and social norms (Salazar et al , 2010), similarly to the chemical one, appears suitable for local forms of self‐organization – think at self‐organized equilibria of web food patterns in ecological niches. Indeed, frameworks inspired by the social metaphor have been effectively experienced in the context of ambient intelligence systems (Agha, 2008; Villalba and Zambonelli, 2011) and of heterogeneous multi‐robot systems (Cakar and Muller‐Schloer, 2009).…”
Section: Natural Metaphors For Pervasive Service Ecosystemsmentioning
confidence: 99%
“…Previous work on convention emergence often assumes that the topology constraining agent interactions is fully observable, allowing highly influential locations to be found easily [11,17,19,21]. However, in many real-world applications such information is not always readily available.…”
Section: Introductionmentioning
confidence: 99%