Cost-based goal recognition for path-planning

Recent developments in plan recognition have established a method of identifying an agent's most probable plan or goal by use of a classical planner and an appeal to the principle of rational action. We examine this technique in the strict context of path-planning. We show that a simpler formula provides an identical result in less than half the time under all but one set of conditions, which we identify. Further, we show that the probability distribution based on this technique is observation-independent and present a revised formula that achieves goal-recognition by reference to the agent's current location only.