Learning and coordinating in a multilayer network

dc.contributor.authorLugo Arocha, Haydeé Corina
dc.contributor.authorSan Miguel, Maxi
dc.date.accessioned2023-06-19T23:55:47Z
dc.date.available2023-06-19T23:55:47Z
dc.date.issued2014
dc.description.abstractWe introduce a two layer network model for social coordination incorporating two relevant ingredients: a) different networks of interaction to learn and to obtain a pay-off, and b) decision making processes based both on social and strategic motivations. Two populations of agents are distributed in two layers with intralayer learning processes and playing interlayer a coordination game. We find that the skepticism about the wisdom of crowd and the local connectivity are the driving forces to accomplish full coordination of the two populations, while polarized coordinated layers are only possible for all-to-all interactions. Local interactions also allow for full coordination in the socially efficient Pareto-dominant strategy in spite of being the riskier one.
dc.description.facultyFac. de Ciencias Económicas y Empresariales
dc.description.facultyInstituto Complutense de Análisis Económico (ICAE)
dc.description.refereedFALSE
dc.description.statusunpub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/27354
dc.identifier.issn2341-2356
dc.identifier.officialurlhttps://www.ucm.es/fundamentos-analisis-economico2/documentos-de-trabajo-del-icae
dc.identifier.relatedurlhttps://www.ucm.es/icae
dc.identifier.urihttps://hdl.handle.net/20.500.14352/41615
dc.issue.number30
dc.language.isoeng
dc.page.total15
dc.relation.ispartofseriesDocumentos de Trabajo del Instituto Complutense de Análisis Económico (ICAE)
dc.rightsAtribución-NoComercial 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttps://creativecommons.org/licenses/by-nc/3.0/es/
dc.subject.jelD69
dc.subject.jelD79
dc.subject.jelC63
dc.subject.keywordDoubt-based decisions
dc.subject.keywordCoordination games
dc.subject.keywordMultilayer network.
dc.subject.ucmEconometría (Economía)
dc.subject.unesco5302 Econometría
dc.titleLearning and coordinating in a multilayer network
dc.typetechnical report
dc.volume.number2014
dcterms.references[1] Levitt, B., March, J.G. Organizational learning. Ann Rev Socio. 14: 319-340 (1988). [2] Delios, A., Henisz, W.J. Political hazards, experience, and sequential entry strategies: the international expassion of Japanese firms 1980-1998. Int Manage J 24:1153-1164 (2003). [3] Schlag, K. Why imitate, and if so, how? A boundedlly rational approach to multi-armed bandits. J Econ Theory 78:130-156 (1998). [4] Vilone, D., Ramasco, J.J., Sánchez, A., San Miguel, M. Social and strategic imitation: the way to consensus. Sci. Rep 2, 686; DOI: 10.1038/srep00686 (2012). [5] Vega-Redondo, F. Economics and the Theory of Games; Cambridge University Press: Cambridge, UK, 2003. [6] Luthi, L., Pestelacci, E., Tomassini, M. Cooperation and community structure in social networks. Physica A 387, 955-966 (2008). [7] Skyrms, B. The Stag Hunt and the Evolution of Social Structure; Cambridge University Press: Cambridge, UK, 2004. [8] Roca, C.P., Cuesta, J.A., Sánchez, A. Evolutionary Game theory: temporal and spatial effects beyond replicator dynamics. Phys. Life Rev. 6, 208-249 (2009). [9] Tomassini, M., Pestelacci, E. Coordination Games on Dynamical Networks. Games 1, 242-261 (2010). [10] Scott, J. Social Network Analysis. SAGE Publications, 2012. [11] Wasserman, S., Faust, K. Social Network Analysis: Methods and Applications. Cambridge University Press, 1994. [12] Zhang, P., Peeta, S., Friesz, T. Dynamic Game Theoretic Model of Multi-Layer Infrastructure Networks. Netw Spat Econ 5, 147-178 (2005). [13] Kivelä, M., Arenas, A., Barthelemy, M., Gleeson, J.P., Moreno, Y., Porter, M.A. Multilayer Networks arXiv:1309.7233 J. Complex Netw. 2(3): 203-271 (2014). [14] Wang, Z. , Szolnoki, A., Perc, M. Interdependent network reciprocity in evolutionary games. Sci. Rep. 3, 1183 (2013). [15] Wang, Z., Szolnoki, A., Perc, M. Optimal interdependence between networks for the evolution of cooperation. Sci. Rep. 3, 2470 (2013). [16] Jiang, L.-L., Perc, M. Spreading of cooperative behaviour across interdependent groups. Sci. Rep. 3, 2483 (2013). [17] Szolnoki, A., Perc, M. Information sharing promotes prosocial behaviour. New J. Phys. 15, 053010 (2013). [18] Wang Z.,Wang L, Perc M. Degree mixing in multilayer networks impedes the evolution of cooperation. Phys. Rev. E 89, 052813 (2014). [19] Granovetter, M. Threshold Models of Collective Behavior. J. Am. Soc. 83, 1420-1443 (1978). [20] Centola, D., Eguíluz, V. M., Macy, M.W. Cascade Dynamics of Complex Propagation. Physica A 374, 449-456 (2007). [21] González-Avella, J.C., Eguíluz, V.M., Marsili, M., Vega-Redondo, F., San Miguel, M. Threshold learning dynamics in social networks. PLoS ONE 6 (5), e20207 (2011). [22] Suchecki, K., Eguíluz, V. M., San Miguel, M. Voter model dynamics in complex networks: Role of dimensionality. Phys. Rev. E} 72, 036132(1-8) (2005). [23] Ramsey FP Truth and probability in Ramsey, 1931. In Braithwaite RB (ed) The foundation of mathematics and other logical essays, Chapter VII. Kegan, Paul, trench $\&$ Co., London; Harcourt, Brace and Company, New York, 156-198. (1926). [24] Cabrales, A., Uriarte, J.R. Doubts and Equilibria. J Evol Econ 23, 783-810 (2013). [25] Gracia-Lázaro, C., Ferrera, A., Ruiz, G., Tarancón, A., Cuesta, J.A., Moreno, Y., Sánchez, A. Heterogeneous networks do not promote cooperation when humans play a Prisoner's Dilemma, PNAS (USA) 109, 12922-12926 (2012) [26] Grujić, J., Fosco, C., Araujo, L., Cuesta, J.A., Sánchez A. Social experiments in the mesoscale: Humans playing a spatial Prisoner's Dilemma PLoS ONE 5 (11), e13749 (2010). [27] Grujić, J., Gracia-Lázaro, C., Traulsen, A., Milinski, M., Semmann, D., Cuesta J.A., Moreno, Y., Sánchez A. A meta-analysis of spatial Prisoner's Dilemma experiments: Conditional cooperation and payoff irrelevance Sci. Rep. 4, 4615 (2014). [28] Vilone, D., Ramasco, J.J., Sánchez, A., San Miguel, M. Social imitation vs strategic choice, or consensus vs cooperation in the networked Prisoner’s Dilemma. Physical Review E 90, 022810 (2014). [29] Holley, R., Liggett, T.M. Ergodic theorems for weakly interacting infinite systems and the Voter Model. Ann. Probab. 3, 643-663 (1975). [30] Nowak, M.A.,May, R.M. Evolutionary games and spatial chaos. Nature 359, 826-829. (1992). [31] Kandori, M., Mailath, G., Rob, R. Learning, mutation, and long-run equilibria in games. Econometrica 61, 29-56. (1993). [32] Ellison, G. Learning, local interaction, and coordination. Econometrica 61, 1047-1071 (1993).
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