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Cognitive Modeling of Complex Dynamic Environments

Christian Lebiere
Postdoctoral Research Associate, Psychology Department, Carnegie Mellon University


Wean Hall 5409


A cognitive architecture consists of a theory of those aspects of human cognition that are relatively constant and general across a wide range of situations, and a set of computational mechanisms to implement that theory and apply it to specific tasks and phenomena. Cognitive architectures are significant to the practice of HCI for two reasons. First, they present a more formal and systematic organization of the relevant aspects of human cognition than the usual collection of microtheories and isolated experimental results. Second, they provide a computational vehicle to apply that knowledge to construct models of user interfaces that deliver precise predictions regarding all measurable aspects of human behavior.

In this talk, I will describe the ACT-R cognitive architecture and its applications to a broad range of tasks. ACT-R is a hybrid architecture that combines a symbolic production system with a subsymbolic, neural-like layer that optimizes itself to the statistical structure of the environment. I will introduce an ACT-R model of a basic paradigm of implicit learning, describe its implications for the learning of location sequences in menu interfaces and discuss its application to the modeling of complex dynamic environments.

Speaker's Bio

Christian Lebiere is a Postdoctoral Research Associate in the ACT-R research group in the Psychology Department at Carnegie Mellon University. He received his B.S. in Computer Science from the University of Liege (Belgium) and his M.S. and Ph.D. from the School of Computer Science at Carnegie Mellon University. His main research interest is cognitive architectures and their applications to psychology, artificial intelligence, economics, decision theory and human-computer interaction.

Christian Lebiere is a candidate for a Research Scientist position in the HCI Institute.