Optimal communication in a noisy and heterogeneous environment

Abstract

Compositionality is a fundamental property of natural language. Explaining its evolution remains a challenging problem because existing explanations require a structured language to be present before compositionality can spread in the population. In this paper, I study whether a communication system can evolve that shows the preservation of topology between meaning-space and signal-space, without assuming that individuals have any prior processing mechanism for compositionality. I present a formalism to describe a communication system where there is noise in signaling and variation in the values of meanings. In contrast to previous models, both the noise and values depend on the topology of the signal-and meaning spaces. I consider a population of agents that each try to optimize their communicative success. The results show that the preservation of topology follows naturally from the assumptions on noise, values and individual-based optimization.