Why semantics when pragmatics? And which? Replicator dynamics meets iterated Bayesian learning

In linguistics, it is common to draw a distinction between semantics and pragmatics. However, the information conveyed by expressions is seldom if ever solely determined by semantics but rather by their pragmatic enrichment. From a functional perspective, the distinction between semantics and pragmatics then raises the challenge to justify the former’s structure in light of the latter.

My aim for this talk is twofold. First, I will lay out a model that integrates iterated learning in the replicator-mutator dynamics, commonly used in evolutionary game theory. The innovation of the model lies in its combination of functional pressure on successful communication via the replicator dynamics, effects of learning biases via iterated Bayesian language learning, and probabilistic models of language use in populations with distinct lexica. Second, I will discuss an application of model to the analysis of a lack of upper-bounds in the literal meaning of (weak) scalar expressions. This application showcases how a learning bias towards simpler semantic representations in tandem with functional pressure may prevent the lexicalization of pragmatic inferences.