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dc.contributor.authorLugo, Haydéees_ES
dc.contributor.authorGonzález-Avella, Juan Carloses_ES
dc.contributor.authorSan Miguel, Maxies_ES
dc.date.accessioned2020-08-21T07:29:38Z-
dc.date.available2020-08-21T07:29:38Z-
dc.date.issued2020-08-11-
dc.identifier.citationChaos 30: 083125 (2020)es_ES
dc.identifier.issn1054-1500-
dc.identifier.urihttp://hdl.handle.net/10261/218343-
dc.description.abstractAnticoordination and chimera states occur in a two-layer model of learning and coordination dynamics in fully connected networks. Learning occurs in the intra-layer networks, while a coordination game is played in the inter-layer network. In this paper, we study the robustness of these states against local effects introduced by the local connectivity of random networks. We identify threshold values for the mean degree of the networks such that below these values, local effects prevent the existence of anticoordination and chimera states found in the fully connected setting. Local effects in the intra-layer learning network are more important than in the inter-layer network in preventing the existence of anticoordination states. The local connectivity of the intra- and inter-layer networks is important to avoid the occurrence of chimera states, but the local effects are stronger in the inter-layer coordination network than in the intra-layer learning network. We also study the effect of local connectivity on the problem of equilibrium selection in the asymmetric coordination game, showing that local effects favor the selection of the Pareto-dominant equilibrium in situations in which the risk-dominant equilibrium is selected in the fully connected network. In this case, again, the important local effects are those associated with the coordination dynamics inter-layer network. Indeed, lower average degree of the network connectivity between layers reduces the probability of achieving the risk-dominant strategy, favoring the Pareto-dominant equilibrium.es_ES
dc.description.sponsorshipHaydée Lugo acknowledges financial support from Ministerio de Ciencia e Innovación (Spain) under Project No. PID2019-109157RB-I00. Maxi San Miguel acknowledges financial support from Agencia Estatal de Investigación (AEI, MCIU, Spain) and Fondo Europeo de Desarrollo Regional (FEDER, UE) under Project PACSS (No. RTI2018-093732-B-C21/C22) and the Maria de Maeztu Program for units of Excellence in R&D (No. MDM-2017-0711).es_ES
dc.language.isoenges_ES
dc.publisherAmerican Institute of Physicses_ES
dc.relationMICIU/ICTI2017-2020/PID2019-109157RB-I00es_ES
dc.relationPID2019-109157RB-I00/AEI/10.13039/501100011033es_ES
dc.relationMICIU/ICTI2017-2020/MDM-2017-0711es_ES
dc.relationMDM-2017-0711/AEI/10.13039/501100011033es_ES
dc.relation.isversionofPublisher's versiones_ES
dc.rightsembargoedAccesses_ES
dc.titleLocal connectivity effects in learning and coordination dynamics in a two-layer networkes_ES
dc.typeartículoes_ES
dc.identifier.doihttp://dx.doi.org/10.1063/5.0006908-
dc.description.peerreviewedPeer reviewedes_ES
dc.relation.publisherversionhttps://doi.org/10.1063/5.0006908es_ES
dc.identifier.e-issn1089-7682-
dc.embargo.terms2021-08-11es_ES
dc.contributor.funderMinisterio de Ciencia, Innovación y Universidades (España)es_ES
dc.contributor.funderAgencia Estatal de Investigación (España)es_ES
dc.contributor.funderEuropean Commissiones_ES
dc.relation.csices_ES
oprm.item.hasRevisionno ko 0 false*
dc.identifier.funderhttp://dx.doi.org/10.13039/501100011033es_ES
dc.identifier.funderhttp://dx.doi.org/10.13039/501100000780es_ES
dc.contributor.orcidLugo, Haydée [0000-0001-5971-2086]es_ES
dc.contributor.orcidSan Miguel, Maxi [0000-0001-6237-425X]es_ES
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