エントロピー多辺最適輸送の情報理論的等価性：マルチエージェント通信の理論
Information-Theoretic Equivalence of Entropic Multi-Marginal Optimal Transport: A Theory for Multi-Agent Communication
エントロピー多辺最適輸送の情報理論的等価性を示し、それを異なる信念を持つエージェント間の通信に応用して、マルチエージェント系における最適性を理論的に証明した。
著者: Shuchan Wang
分類: cs.IT, cs.AI, cs.RO, math.IT
原文アブストラクト
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.