Project Profile

This IGERT project examines the problem of sequential decision-making as a unifying framework for the study of several central topics in cognitive science: selective attention, navigation, language processing, and the coordination of action in multiple-agent... more »

This IGERT project examines the problem of sequential decision-making as a unifying framework for the study of several central topics in cognitive science: selective attention, navigation, language processing, and the coordination of action in multiple-agent groups. The overarching question our students are trained to investigate is the following: how is it possible for an agent to decide what actions to take to achieve long-term goals’ We recognize that decision-making in complex environments is a sequential process, involving a series of episodes in which an agent, based on information available through its senses and stored in memory, selects the action appropriate for its goals. The problem is made difficult by perceptual uncertainty arising from sensory limitations and environmental complexity, by the challenge of sorting through the large space of actions available, and by inherent delays in feedback about the long-term consequences of actions. A wide variety of fundamental cognitive tasks can be cast as sequential decision-making problems. Understanding how such problems may be solved will be a critical component of a general theory of intelligent behavior in organisms, and will be essential for the design of truly intelligent machines. To study these problems, we adopt a comparative approach, combining insights from a range of model systems, including humans, non-human animals, robots, and intelligent software agents. This multidisciplinary framework will enable students to integrate ideas and methods from different fields that have been concerned with the study of sequential decision-making (psychology, behavioral biology, linguistics, and computer science), but that have so far remained largely separate. The training program is designed to create a new generation of scientists trained in this innovative, multidisciplinary approach. Graduate training will be focused on fundamental disciplinary education, a common set of courses focused on the sequential decision-making framework, and a strong emphasis on mentored, interdisciplinary research activities that span each student’s entire graduate program.

IGERT is an NSF-wide program intended to meet the challenges of educating Ph.D. scientists and engineers with the multidisciplinary backgrounds and the technical, professional, and personal skills needed for the career demands of the future. The program is intended to catalyze a cultural change in graduate education by establishing new, innovative models for graduate education and training in a fertile environment for collaborative research that transcends traditional disciplinary boundaries. In the fourth year of the program, awards are being made to twenty-two institutions for programs that collectively span all areas of science and engineering supported by NSF. The intellectual foci of this specific award reside in the Directorates for Social, Behavioral, and Economic Sciences; Computer and Information Science and Engineering; Engineering; Biological Sciences; and Education and Human Resources. « less

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