RT Journal Article
T1 Learning and coordinating in a multilayer network
A1 Lugo Arocha, Haydeé Corina
A1 San Miguel, Maxi
AB 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.
PB Nature Publishing Group
SN 2045-2322
YR 2015
FD 2015
LK https://hdl.handle.net/20.500.14352/34199
UL https://hdl.handle.net/20.500.14352/34199
LA eng
NO Ministerio de Ciencia e Innovación (MICINN)
NO Ministerio de Economía y Competitividad (MINECO)
NO European Regional Development Fund
NO Comisión Europea
DS Docta Complutense
RD 8 sept 2025