A mathematical theory of cooperative communication
This provides a foundational theory for understanding cooperative communication in human cognition and human-machine interaction, though it is incremental in extending existing models mathematically.
The paper tackled the lack of a mathematical foundation for cooperative communication by developing a framework based on optimal transport theory, deriving prior models as special cases and proving robustness and instability properties, with computational simulations showing fit to human behavior.
Cooperative communication plays a central role in theories of human cognition, language, development, culture, and human-robot interaction. Prior models of cooperative communication are algorithmic in nature and do not shed light on why cooperation may yield effective belief transmission and what limitations may arise due to differences between beliefs of agents. Through a connection to the theory of optimal transport, we establishing a mathematical framework for cooperative communication. We derive prior models as special cases, statistical interpretations of belief transfer plans, and proofs of robustness and instability. Computational simulations support and elaborate our theoretical results, and demonstrate fit to human behavior. The results show that cooperative communication provably enables effective, robust belief transmission which is required to explain feats of human learning and improve human-machine interaction.