  By using communication between multiple agents in multi-agent environments,
one can reduce the effects of partial observability by combining one agent's
observation with that of others in the same dynamic environment. While a lot of
successful research has been done towards communication learning in cooperative
settings, communication learning in mixed cooperative-competitive settings is
also important and brings its own complexities such as the opposing team
overhearing the communication. In this paper, we apply differentiable
inter-agent learning (DIAL), designed for cooperative settings, to a mixed
cooperative-competitive setting. We look at the difference in performance
between communication that is private for a team and communication that can be
overheard by the other team. Our research shows that communicating agents are
able to achieve similar performance to fully observable agents after a given
training period in our chosen environment. Overall, we find that sharing
communication across teams results in decreased performance for the
communicating team in comparison to results achieved with private
communication.
