#Monica L. Martinez-Canales Computer Science Research Institute Seminar Series ___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________ Title Uncertain Reasoning in Open Worlds Speaker Stuart Russell Computer Science Division University of California, Berkeley russell@cs.berkeley.edu Date July 22, 2004 Time 10-11am (PT) 11-12am (MT) Location 921/137 (CA) 980/24 (NM) Abstract There has been a good deal of progress in recent years on the problem of uncertain reasoning about objects and relations. With few exceptions, however, work in this area assumes *unique names* (every term in the modeling language refers to a distinct object) and *domain closure* (there are no objects besides those named by terms in the language). These assumptions are untenable in many real-world settings, where unknown objects may exist and there is uncertainty as to the true identity of objects. Such settings include surveillance, link detection, and information extraction. I will present a formal language for specifying probability models that allow for unknown objects and identity uncertainty, with applications to wide-area freeway traffic monitoring and bibliographic citation databases. About the Speaker Stuart Russell received his B.A. with first-class honours in physics from Oxford University in 1982, and his Ph.D. in computer science from Stanford in 1986. He then joined the faculty of the University of California at Berkeley, where he is a professor of computer science, director of the Center for Intelligent Systems, and holder of the Smith--Zadeh Chair in Engineering. In 1990, he received the Presidential Young Investigator Award of the National Science Foundation, and in 1995 he was cowinner of the Computers and Thought Award. He was a 1996 Miller Professor of the University of California and was appointed to a Chancellor's Professorship in 2000. In 1998, he gave the Forsythe Memorial Lectures at Stanford University. He is a Fellow and former Executive Council member of the American Association for Artificial Intelligence and a Fellow of the Association for Computing Machinery. He has published over 100 papers on a wide range of topics in artificial intelligence. His books include "The Use of Knowledge in Analogy and Induction" (Pitman, 1989), "Do the Right Thing: Studies in Limited Rationality" (with Eric Wefald, MIT Press, 1991), and "Artificial Intelligence: A Modern Approach" (with Peter Norvig, Prentice Hall, 1995, 2003). Host Keith B. Vanderveen, kbvande@sandia.gov, 925-294-3207, or Monica Martinez-Canales, mmarti7@sandia.gov, 925-294-3157 This seminar series is hosted by the Computational Sciences and Mathematics Research Department at Sandia National Labs in Livermore, CA. This seminar is funded by the Computer Science Research Institute (CSRI). To schedule a time to meet with the speaker before or after the talk, please make arrangements with the host listed above. Visitors from outside Sandia require at least 3 days notice in order to attend. For more information, see http://csmr.ca.sandia.gov/csri/visitor.html. The exception is any U.S. Citizens with a valid DOE badge. 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