RT Report
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.
SN 2341-2356
YR 2014
FD 2014
LK https://hdl.handle.net/20.500.14352/41615
UL https://hdl.handle.net/20.500.14352/41615
LA eng
DS Docta Complutense
RD 25 abr 2025