Computational foundations of intelligent sensing, reasoning, and action
I’m interested in computational foundations of intelligent sensing, reasoning, and action–with a particular focus on methods for grappling with uncertainty about environments or situations. I’m also interested in models of human cognition, and in developing computational systems that leverage insights about cognition to help people to achieve their goals. Much of my work makes use of probability and decision theory, decision analysis, and, in particular, Bayesian and decision-theoretic principles. My research spans both theoretical issues and concrete, real-world applications. I’m interested in information triage and alerting that takes human attention into consideration, spanning work on notification systems, multitasking, and psychological studies of interruption and recovery.
Other interests include principles of mixed-initiative interaction that can support fluid, efficient collaborations between people and computing systems, methods for guiding computer actions in accordance with the preferences of people, search and information retrieval, and collaboration. I’ve also been long interested in offline and real-time optimization of the expected value of computational systems under limited and varying resources. Areas of concentration in this realm include flexible or anytime computation, ideal metareasoning for guiding computation, compilation for reducing real-time deliberation, ongoing, continual computation, and the construction of bounded-optimal reasoning systems–systems that maximize the expected utility of the people they serve, given the expected costs of reasoning, the problems encountered over time, and assertions about a system’s constitution. Research in this arena includes tackling hard reasoning problems with learning and decision making methods. I’m serving as President-Elect of the American Association for Artificial Intelligence. See the AAAI web pages for more information on research and events in the AI community.