Emergence of Conventions in Conflict Situations in Complex Agent Network Environments

We modelled the conflict situation using a Markov game on various complex networks and investigated the emergence of conventions for conflict resolutions in agent networks with various structures through pairwise reinforcement learning. We found the network structure strongly affected their emergence and the agents could sometimes learn no conventions although they could learn locally consistent actions for resolutions.