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      Anytime Decision Making with Imprecise Probabilities

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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 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.

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          Author and article information

          Journal
          2013-02-27
          Article
          1302.6837
          eb815e9b-5723-4c7b-a939-62438c95dda3

          http://arxiv.org/licenses/nonexclusive-distrib/1.0/

          History
          Custom metadata
          UAI-P-1994-PG-470-477
          Appears in Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence (UAI1994)
          cs.AI
          auai

          Artificial intelligence
          Artificial intelligence

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