Formal models play a critical role in advancing scientific understanding.  Together with objective methods of measurement, the formal expression of understanding distinguishes scientific knowledge from other approaches to understanding.  Formal models have long played an important role in efforts to understand human sentence processing, and there is a strong belief among researchers in this area that future advances in understanding can be accelerated by broader use of formal models that provide explicit characterizations of the cognitive processes that underlie the ability to use language.  Further, there is recognition that broader, more effective use of formal models depends on enhancing and disseminating knowledge about formal models to researchers studying human sentence processing. 

This special session will focus on the development and use of formal models in the understanding of human language and cognition more generally.  Broad presentations by invited speakers will anchor the session which will also include peer-reviewed contributions.  Invited speakers include:

Dan Jurafsky (Stanford University)
Erik Reichle (University of Pittsburgh)
Josh Tenenbaum (Massachusetts Institute of Technology)
Matt Traxler (University of California, Davis)