Communicating Agents in a Shared World
Tuesday, November 4, 2003 - 10:15am - 10:50am
Natalia Komarova (Institute for Advanced Study)
We consider the problem of linguistic agents that communicate with each other about a shared world. We develop a formal notion of a language as a set of probabilistic associations between form (lexical or syntactic) and meaning (semantic) that has general applicability. Using this notion, we define a natural measure of the mutual intelligibility, F(L,L'), between two agents, one using the language L and the other using L'. A natural question is this: Given a language L, what language L' maximizes mutual intelligibility with L? We find surprisingly that L' need not be the same as L and we present algorithms for approximating L' arbitrarily well. Next, we consider a population of linguistic agents that learn from each other and evolve over time. Will the community converge to a shared language and what is the nature of such a language? We characterize the evolutionarily stable states of a population of linguistic agents in a game-theoretic setting. Our analysis is relevant for a number of areas in natural and artificial communication where one studies the design, learning, and evolution of linguistic communication systems.