Reflection and Action Under Scarce Resources: Theoretical Principles and Empirical Study

Abstract

We define and exercise the expected value of computation as a fundamental component of reflection about alternative inference strategies. We present a portion of Protos research focused on the interlacing of reflection and action under scarce resources, and discuss how the techniques have been applied in a high-stakes medical domain. The work centers on endowing a computational agent with the ability to harness incomplete characterizations of problemsolving performance to control the amount of effort applied to a problem or subproblem, before taking action in the world or turning to another problem. We explore the use of the techniques in controlling decision-theoretic inference itself, and pose the approach as a model of rationality under scarce resources. 1 Reflection and Flexibility Reflection about the course of problem solving and about the interleaving of problem solving and physical activity is a hallmark of intelligent behavior. Applying a portion of available reasoning resources to consider the utility of alternative inference strategies or the value of continuing to refine a result before acting enables a computational agent to generate custom-tailored approaches to a wide variety of problems, under different time pressures. Such flexibility can be especially useful in light of uncertain deadlines and challenges. Uncertainty about problems and problem solving plagues simple agents immersed in complex environments. Constraints on an agent's reasoning and representation resources lead to inescapable uncertainties about the problems that may be faced and about the value of future reasoning in solving those problems. The Protos project has pursued the use of decision theory for real-time control and offline problem-*This work was supported by a NASA Fellowship under