Anytime Decision Making with Imprecise Probabilities
Artificial Intelligence
2013-02-28 v1
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 1991. 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.
Keywords
Cite
@article{arxiv.1302.6837,
title = {Anytime Decision Making with Imprecise Probabilities},
author = {Michael Pittarelli},
journal= {arXiv preprint arXiv:1302.6837},
year = {2013}
}
Comments
Appears in Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence (UAI1994)