Toward a Large-Scale Model of Language Comprehension in ACT-R 6

We are developing a large-scale model of language comprehension in ACT-R 6 for use in the creation of a synthetic teammate that can function as the Air Vehicle Operator (AVO) in a three-person simulation of an Unmanned Aerial Vehicle (UAV) team performing a reconnaissance mission. The use of ACT-R 6 to implement the core components of this system reflects the strong cognitive modeling orientation of this research. However, the focus is on creating cognitively plausible linguistic and associated nonlinguistic representations, rather than modeling the finegrained time course of language processing as is more typical of ACT-R models. In this regard, an empirical study aimed at discovering evidence of linguistic representations is discussed. Beside the focus on linguistic and non-linguistic representations, the large-scale nature of this effort distinguishes it from typical cognitive modeling research.