Proceedings of the Annual Meeting of the Cognitive Science Society

Word learning involves mapping observable words to unob-servable speaker intentions. The ability to infer referential in-tentions in turn has been shown to depend in part on accessto language. Thus, word learning and intention-reading co-develop. To explore this interaction, we present an agent-basedmodel in which an individual simultaneously learns a lexiconand learns about the speaker’s perspective, given a shared con-text and the speaker’s utterances, by performing Bayesian in-ference. Simulations with this model show that (i) lexicon-learning and perspective-learning are strongly interdependent:learning one is impossible without some knowledge of theother, (ii) lexicon- and perspective-learning can bootstrap eachother, resulting in successful inference of both even when thelearner starts with no knowledge of the lexicon and unhelpfulassumptions about the minds of others, and (iii) receiving ini-tial input from a ‘helpful’ speaker (who adopts the learner’sperspective on the world) paves the way for later learning fromspeakers with perspectives which diverge from the learner’s.This approach represents a first attempt to model the hypoth-esis that language and mindreading co-develop, and a first ex-ploration of the implications for theories of word learning andmindreading development.