This project is being funded through the Learning and Intelligent Systems (LIS) initiative. It is interdisciplinary research in the knowledge, processing, and learning of language. It proceeds from a framework utilizing results from mathematical statistics, adaptive systems, and formal learning theory which provide a means of treating language as a kind of statistical optimization. Previous work by the principal investigator on the integration of linguistic theory with optimization principles in neural networks has led to this new grammar formalism, optimality theory, which has had considerable impact on many aspects of the study of human language, including learning. Recently developed methods of psychological experimentation now provide reliable data on the process of language learning, even in infants. This research brings together these experimental methods for observing real-time processing and learning of language, computational methods of research on optimization and automatic language processing, and linguistic methods for studying the structure of the representations essential for human language. The investigators bring not only expertise in the contributing disciplines, but also considerable experience in interdisciplinary collaboration. The results of this research will help us to explain the mystery of how humans - and possibly artificial systems - can learn to use and understand languages.
