A Model for Projection and Action

Abstract

In designing autonomous agents that deal competently with issues involving time and space, there is a tradeoff to be made between guaranteed response-time reactions on the one hand, and flexibility and expressiveness on the other. We propose a model of action with probabilistic reasoning and decision analytic evaluation for use in a layered control architecture. Our model is well suited to tasks that require reasoning about the interaction of behaviors and events in a fixed temporal horizon. Decisions are continuously reevaluated, so that there is no problem with plans becoming obsolete as new information becomes available. In this paper, we are particularly interested in the trade-offs required to guarantee a fixed reponse time in reasoning about nondeterministic cause-and-eflect relationships. By exploiting approximate decision making processes, we are able to trade accuracy in our predictions for speed in decision making in order to improve expected performance in dynamic situations.