Learning and coordinating in a multilayer network
| dc.contributor.author | Lugo Arocha, Haydeé Corina | |
| dc.contributor.author | San Miguel, Maxi | |
| dc.date.accessioned | 2023-06-19T13:39:03Z | |
| dc.date.available | 2023-06-19T13:39:03Z | |
| dc.date.issued | 2015 | |
| dc.description.abstract | We 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.department | Depto. de Análisis Económico y Economía Cuantitativa | |
| dc.description.faculty | Fac. de Ciencias Económicas y Empresariales | |
| dc.description.refereed | TRUE | |
| dc.description.sponsorship | Ministerio de Ciencia e Innovación (MICINN) | |
| dc.description.sponsorship | Ministerio de EconomÃa y Competitividad (MINECO) | |
| dc.description.sponsorship | European Regional Development Fund | |
| dc.description.sponsorship | Comisión Europea | |
| dc.description.status | pub | |
| dc.eprint.id | https://eprints.ucm.es/id/eprint/60273 | |
| dc.identifier.doi | 10.1038/srep07776 | |
| dc.identifier.issn | 2045-2322 | |
| dc.identifier.officialurl | https://doi.org/10.1038/srep07776 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14352/34199 | |
| dc.journal.title | Scientific reports | |
| dc.language.iso | eng | |
| dc.page.final | 7 | |
| dc.page.initial | 1 | |
| dc.publisher | Nature Publishing Group | |
| dc.relation.projectID | ECO2013-42710-P | |
| dc.relation.projectID | FIS2012- 30634 | |
| dc.relation.projectID | FP7-ICT-318132 | |
| dc.rights | Atribución-NoComercial-SinDerivadas 3.0 España | |
| dc.rights.accessRights | open access | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/3.0/es/ | |
| dc.subject.keyword | Computer simulation | |
| dc.subject.keyword | Game theory | |
| dc.subject.keyword | Humans | |
| dc.subject.keyword | Learning | |
| dc.subject.keyword | Theoretical models | |
| dc.subject.keyword | Social support | |
| dc.subject.keyword | Time factors | |
| dc.subject.ucm | Teoría de Juegos | |
| dc.subject.ucm | Econometría (Economía) | |
| dc.subject.ucm | Aprendizaje | |
| dc.subject.unesco | 1207.06 Teoría de Juegos | |
| dc.subject.unesco | 5302 Econometría | |
| dc.subject.unesco | 6104.03 Leyes del Aprendizaje | |
| dc.title | Learning and coordinating in a multilayer network | |
| dc.type | journal article | |
| dc.volume.number | 5 | |
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| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | 893acf3a-d00d-4165-89f1-74fe5ad70ae1 | |
| relation.isAuthorOfPublication.latestForDiscovery | 893acf3a-d00d-4165-89f1-74fe5ad70ae1 |
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