Information Seeking, Visualization, and Decision-Making
Delivering the right information to the "right people in the right time" for responding to extreme events has become increasingly difficult due to the explosion of information and the increasing severity of these events' impacts. Drawing from studies about effective human team performance and theories about human decision making under time stress, we have developed a cognitive agent architecture inspired by Recognition-Primed Decision (RPD), which is a naturalistic decision making model. The RPD model provides the context of decision-making, from which the agent dynamically identifies relevant information, proactively seek and share them among a distributed decision-making team for damage assessments and resource allocations.
Speaker: Dr. John Yen
Associate Dean for Research and Graduate Programs, University Professor of Information Sciences and Technology, College of Information Sciences and Technology, The Pennsylvania State University.
Dr. John Yen received his B.S. in Electrical Engineering from National Taiwan University, Taipei, Taiwan in 1980, his M.S. in Computer Science from University of Santa Clara, CA in 1982, and his Ph.D. in Computer Science from the University of California, Berkeley in 1986. He is currently the Associate Dean for Research and Graduate Programs and the University Professor of College of Information Sciences and Technology (IST) at the Pennsylvania State University. He is also the founder and the Director of Laboratory for Intelligent Agents, one of the research labs of IST@PennState.
Google Tech Talks
August 27, 2008