Abstract

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. 1 Computation Under Uncertainty We are investigating the decision-theoretic control of problem solving under varying constraints in resources required for reasoning, such as time and memory. This work is motivated by the pursuit of formal models of rational decision making under resource constraints and our goal of extending foundational work on normative rationality to computational agents. We describe here a portion...

Citations

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