From partners to populations: A hierarchical Bayesian account of coordination and convention

Abstract

Languages are powerful solutions to coordination problems: they provide stable, shared expectations about how the words we say correspond to the beliefs and intentions in our heads. Yet language use in a variable and non-stationary social environment requires linguistic representations to be flexible: old words acquire new ad hoc or partner-specific meanings on the fly. In this paper, we introduce a hierarchical Bayesian theory of convention formation that aims to reconcile the long-standing tension between these two basic observations. More specifically, we argue that the central computational problem of communication is not simply transmission, as in classical formulations, but learning and adaptation over multiple timescales. Under our account, rapid learning within dyadic interactions allows for coordination on partner-specific common ground, while social conventions are stable priors that have been abstracted away from interactions with multiple partners. We present new empirical data alongside simulations showing how our model provides a cognitive foundation for explaining several phenomena that have posed a challenge for previous accounts: (1) the convergence to more efficient referring expressions across repeated interaction with the same partner, (2) the gradual transfer of partner-specific common ground to novel partners, and (3) the influence of communicative context on which conventions eventually form.

The complexity of a language is shaped by the communicative needs of its users and by the hierarchical nature of their social inferences

“…in communities with heterogeneous communicative needs. Meanwhile, an account of how partner-specific knowledge can become conventionalized into population-level expectations through adaptation of the lexicon has been proposed by Hawkins et al (2019) and Hawkins et al (2021). They formulate their theory in a hierarchical model, and also show (similarly to Winters et al, 2015) that conventions are sensitive to the context of communication.…”