Winning an Election: On Emergent Strategic Communication in Multi-Agent Networks

Humans use language to collectively execute abstract strategies besides using it as a referential tool for identifying physical entities. In this paper, we study the role of emergent languages in discovering and implementing strategies. We formulate the problem using a voting game where two candidate agents contest in an election with the goal of convincing population members (other agents), that are connected to each other via an underlying network, to vote for them. To achieve this goal, agents are only allowed to exchange messages in the form of sequences of discrete symbols. Using our proposed framework, we answer the following questions: (i) Do the agents learn to communicate in a meaningful way? (ii) Does the system evolve as expected under various reward structures? (iii) How is the emergent language affected by the community structure in the network? To the best of our knowledge, we are the first to study emergence of communication among networked agents for discovering and implementing strategies.