A question-answering system designed by researchers from UMD and the University of Colorado holds its own against a top human team.
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.
Language science is by nature multidisciplinary and our programs support students in actively crossing departmental and university boundaries. The language science initiative provides students with the flexibility to create individualized programs of study involving combinations of faculty mentors. The list of programs and specializations below is just a starting point, and our current students and faculty mentors are happy to answer questions about the programs and about particular areas of interest.
LSD marked the 1-year anniversary of the Maryland Language Science Center, showcasing many ideas and initiatives launched over the past year.