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Plenary Speakers 
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 Herb Simon Using Machine Learning to Understand Human Learning An important application of AI methods has been to model human learning processes. Human learning probably employs several different, and complementary mechanisms: to differentiate and recognize stimuli, to learn new procedures and compile them for greater efficiency, to build associative information stores. The talk will survey a range of methods, including serial (symbolic) and parallel (connectionist) methods, that have been proposed, and the evidence linking them to empirical data on human learning.
Herbert A. Simon's research has ranged from computer science to psychology, administration, and economics. The thread of continuity has been human decision-making and problem-solving processes, and extensive use of the computer for simulating human thinking. Born in 1916 in Milwaukee, Wisconsin, Simon was educated at the University of Chicago. Since 1949, he has been on the faculty of Carnegie Mellon University, where he is Richard King Mellon University Professor of Computer Science and Psychology. In 1978, he received the Alfred Nobel Memorial Prize in Economic Sciences, and in 1986 the National Medal of Science. More Information Contact conald@cs.cmu.edu for more information The conference is sponsored by CMU's newly created Center for Automated Learning and Discovery. |
