Rational Decision-Making In Resource-Bounded Agents1

The objective of this paper is to construct an implementable theory of rational decision-making for cognitive agents subject to realistic resource constraints. It is argued that decision-making should select actions indirectly by selecting plans that prescribe them. It is also argued that although expected values provide the tool for evaluating plans, plans cannot be compared straightforwardly in terms of their expected values, and the objective of a realistic agent cannot be to find optimal plans. The theory of Locally Global planning is proposed as a realistic alternative to standard "maximizing" theories of rational decision-making. 1. Rational Cognition Rational agents think about the world, evaluate various aspects of it, reflect upon how they might make it more to their liking, and act accordingly. Then the cycle repeats. This is the doxastic-conative loop, diagrammed in figure one. The defining characteristic of cognitive agents is that they implement the doxastic-conative loop by thinking about the world and acting upon it in response to their deliberations. Both human beings and the autonomous rational agents envisaged in AI are cognitive agents in this sense. 1 This work was supported by NSF grant no. IRI-IIS-0080888.