August 16, 2010 | 7:48 am
Posted by Adam Wills
UCLA professor and Journal columnist Judea Pearl has won the Rumelhart Prize from the Cognitive Science Society for his research in artificial intelligence and systems that reason plausibly from uncertain evidence. The prize, which carries a $100,000 monetary award, is given to researchers who have made the greatest contributions to determining how our minds work. The announcement was made during the group’s annual meeting, CogSci 2010, in Portland, Ore., Aug. 12-14.
Pearl’s work on graphical models addresses the dynamics of beliefs and the analysis of causality. Graphical models have had a transformative impact across many disciplines—including statistics, machine learning, epidemiology and psychology—and they are the foundation of the recent emergence of a branch of cognitive science representing probabilistic relationships, such as those between symptoms and diseases, and skills and earnings. Pearl has pioneered the development of graphical models, including a class of graphical models known as Bayesian networks, which can be used to represent and draw inferences from probabilistic knowledge in a highly transparent and computationally efficient way.
“Dr. Pearl’s path-breaking work has been enormously influential. He provides one of the most prominent hypotheses about the workings of the human mind, and has helped reinvigorate causality research,” William Bechtel, Rumelhart Prize committee member and philosophy professor at the University of California at San Diego, said in a statement. “People often say, ‘You can’t derive causation from correlation.’ But Dr. Pearl’s research shows that you can logically determine causal relations from correlations if you have many interrelated variables and you make some minimal assumptions about how causal processes operate. The Cognitive Science Society is proud to recognize our esteemed colleague and the very high bar he has set with his research achievements.”
“Given that our knowledge of the world is important primarily because it serves as the basis for action, building a theory of causality is, I believe, of central importance to understanding human cognition,” Pearl said. “The inspiration for my works came from cognitive science and from the 1970s papers of David Rumelhart, while the applicability of my research is in part thanks to collaboration I’ve received within the robotics, statistical and epidemiology communities. I’m honored to receive the Rumelhart Prize and accept this recognition in the spirit of continued collaboration with other facets of science that are helping solve the ever-fascinating mysteries of how the mind works.”
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