Signaling under uncertainty

What is conveyed often goes beyond what is said. Rather than avoiding it, natural communication seems to thrive in the implicit; in the unsaid; in the contextually determined. This investigation centers around this issue by asking why and under which conditions language (use) may come to leverage or accommodate the unsaid when matters could be conveyed more explicitly. More precisely, at a fundamental level, we seek to better understand why there is a division of labor between semantics and pragmatics. We do so by looking at the conditions under which properties that draw from this division arise, which we analyze by combining, in novel ways, game-theoretic models of rational language use, reinforcement learning, (iterated) Bayesian learning, and population dynamics such as the replicator-mutator dynamic. Our analysis traces linguistic change at the level of iterated interactions as well as at that of populations. Both levels come with their own perspective and thereby shed their own light on a given linguistic property. This allows us to explore different yet connected answers to questions such as why natural communication is rife with semantic ambiguity; under which conditions systematic pragmatic inferences may (fail to) lexicalize; and, more generally, what kinds of divisions of labor between semantics and pragmatics we can expect to arise from pressures and environmental factors that shape language