Distributed Coordination and Network Structure: Experimental Results from Simulation

Coordination is an important phenomena occurring in a wide variety of social and technical systems. We use simulation to examine the ways in which one important system property, the interaction network, effects overall levels of coordination. In particular, we survey the performance of six different learning algorithms, including reasonable strategies and no regret strategies on networks generated by six different algorithms. Our results suggest that no-regret mechanisms not only perform better but also come closer to replicating human behavior in the network coordination task.