  In this paper, we propose our information-theoretic equivalence of entropic
multi-marginal optimal transport (MOT). This equivalence can be easily reduced
to the case of entropic optimal transport (OT). Because OT is widely used to
compare differences between knowledge or beliefs, we apply this result to the
communication between agents with different beliefs. Our results formally prove
the statement that entropic OT is information-theoretically optimal given by
Wang et al. [2020] and generalize it to the multi-agent case. We believe that
our work can shed light on OT theory in future multi-agent teaming systems.
