  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.
