Norm emergence through In uence-based aggregative learning in Mobile agent network

Abstract

Social norm have often been used to promote cooperation and coordination and to avoid unnecessary con icts in multiagent systems. Furthermore, interaction between agents is ususally based on social network topology, that is, how individuals are connected. Thus, many studies are dedicated to the emergence of norms in these complex networks, but few of them focused on dynamically changing networks. This paper extends our previous study, in uence-based aggregative learning (IAL), which is framework to facilitate the emergence of social norms in static complex network, to apply to changing networks. Then, we experimentally indicate that the norm can emerge in the networks of agents by the extended IAL.