Cognitive Science Colloquium
Noah Goodman
Stanford University
Uncertainty in language and thought

Probabilistic models of human cognition have been widely successful at capturing the ways that people represent and reason with uncertain knowledge. In this talk I will explore the ways that this probabilistic approach can be applied to systematic and productive reasoning -- in particular, natural language pragmatics and semantics. I will first describe how probabilistic programming languages provide a formal tool encompassing probabilistic uncertainty and compositional structure. I'll illustrate with a examples from inductive reasoning and social cognition. I will then present a framework for language understanding that views literal sentence meaning through probabilistic conditioning and pragmatic enrichment as recursive social reasoning grounded out in literal meaning. I will consider how this framework provides a theory of the role of context in language understanding, focusing on examples from implicature, vague adjectives, and figurative speech (hyperbole and irony).

Thursday, February 5, 2015
3:30pm - 5:30pm

Bioscience Research Building 1103