easoning Under Varying and U esource Constraints

We describe the use of decision-theory to optimize the value of computation under uncertain and varying resource limitations. The research is motivated by the pursuit of formal models of rational decision making for computational agents, centering on the explicit consideration of preferences and resource availability. We focus here on the importance of identifying the multiattribute structure of partial results generated by approximation methods for making control decisions. Work on simple algorithms and on the control of decision-theoretic inference itself is described.