Anytime decision making with imprecise probabilities

Authors:
Michael Pittarelli
Affiliations:
Computer Science Department, SUNY Institute of Technology, Utica, NY
Venue:
UAI'94 Proceedings of the Tenth international conference on Uncertainty in artificial intelligence
Year:
1994

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Abstract

This paper examines methods of decision making that are able to accommodate limitations on both the form in which uncertainty pertaining to a decision problem can be realistically represented and the amount of computing time available before a decision must be made. The methods are anytime algorithms in the sense of Boddy and Dean [1989]. Techniques are presented for use with Frisch and Haddawy's [1992] anytime deduction system, with an anytime adaptation of Nilsson's [1986] probabilistic logic, and with a probabilistic database model.