In Memoriam: Henry Kyburg
Senior Research Scientist
1928-2007. Ph. D. (1955) (Philosophy) Columbia. Assistant Professor (Mathematics) Wesleyan University (58-61). Research Associate, Rockefeller Institute (61-62). Associate Professor (Mathematics and Philosophy) University of Denver, (62-63). Associate Professor (Philosophy) Wayne State University (63-65). Professor (Philosophy) University of Rochester (65-present); Burbank Professor of Moral and Intellectual Philosophy (82-present); Professor of Computer Science (86-present); Fellow American Association for the Advancement of Science (1982); Fellow American Academy of Arts and Sciences (1995).
Both we and our machines must be able to take account of uncertainty, for reasoning, for planning, in knowledge representation. Dealing with uncertainty raises a number of fundamental questions:
How do you best represent uncertainty in a formal framework? Various suggestions have been made; it is turning out to be the case that most are reducible to probabilistic measures. Is probability objective or subjective? Purely subjective views of probability are of questionable use; but objective logical views are not yet well developed. That is a task we are currently working on.
Not only do we want to represent uncertainty in a fixed body of knowledge, but we want to use new evidence to update those probabilities. Various updating procedures have been proposed. Analysis reveals that they have much in common, but efficient updating is still a goal we are working on.
Finally, the reason for the intelligent use of uncertainty is for making decisions. But the appropriate decision theory depends on the treatment of uncertainty, and so is also an active area of research.
Henry E. Kyburg, Jr. The Logical Foundations of Statistical Inference, Reidel, Dordrecht, 1974.
Henry E. Kyburg, Jr. The Reference Class. Philosophy of Science 50, 374-397, 1983.
Henry E. Kyburg, Jr. Theory and Measurement, Cambridge University Press, 1984.
Henry E. Kyburg, Jr. Bayesian and Non-bayesian Evidential Updating. AI Journal 31, 271-294, 1987.
Henry E. Kyburg, Jr. Science and Reason, Oxford University Press, 1990.
Henry E. Kyburg, Jr. Believing on the Basis of Evidence, Computational Intelligence 10, 1994, pp. 3-21, 107-115.
Henry E. Kyburg, Jr. Uncertain inferences and uncertain conclusions. Twelfth Conference on Uncertainty in Artificial Intelligence, pages 365-372, 1996.
Henry E. Kyburg, Jr. Combinatorial semantics: Semantics for frequent validity. Computational Intelligence, to appear.