@Article{delgado02a,
  author =	 {Jordi Delgado},
  title =	 {Emergence of social conventions in complex networks},
  googleid =	 {-ZCliIbRyPEJ:scholar.google.com/},
  journal =	 {Artificial Intelligence},
  year =	 2002,
  volume =	 141,
  pages =	 {171--185},
  abstract =	 {The emergence of social conventions in multi-agent
                  systems has been analyzed mainly in settings where
                  every agent may interact either with every other
                  agent or with nearest neighbours, according to some
                  regular underlying topology. In this note we argue
                  that these topologies are too simple if we take into
                  account recent discoveries on real networks. These
                  networks, one of the main examples being the
                  Internet, are what is called complex, that is,
                  either graphs with the small-world property or
                  scale-free graphs. In this note we study the
                  efficiency of the emergence of social conventions in
                  complex networks, that is, how fast conventions are
                  reached. Our main result is that complex graphs make
                  the system much more efficient than regular graphs
                  with the same average number of links per
                  node. Furthermore, we find out that scale-free
                  graphs make the system as efficient as fully
                  connected graphs.},
  keywords =     {multiagent learning game-theory},
  doi =		 {10.1016/S0004-3702(02)00262-X},
  url =		 {http://jmvidal.cse.sc.edu/library/delgado02a.pdf},
  cluster = 	 {17422405534231138553},
}