In search for a cognitively plausible formal model of reasoning about uncertainty in common ground, this project addresses the problems of representational and of inferential complexity that naive approaches face. By drawing on tenets from Relevance Theory, common ground is treated as inferred, rather than as given (ex ante). The project aims to develop probabilistic models of this inference process by drawing inspiration from resource-bounded rationality, dual-processing accounts of reasoning and formal representations of inattentiveness. Novel experimental tasks are developed to test downstream predictions from our probabilistic models.
