Describing Plan Recognition as Nonmonotonic Reasoning and Belief Revision

We provide a characterization of plan recognition in terms of a general framework of belief revision and non-monotonic reasoning. We adopt a generalization of classical belief revision to describe a competence model of plan recognition which supports dynamic change to all aspects of a plan recognition knowledge base, including background knowledge, action descriptions and their relationship to named plans, and accumulating sets of observations on agent actions. Our plan recognition model exploits the underlying belief revision model to assimilate observations, and answer queries about an agent's intended plans and actions. Supporting belief states are determined by observed actions and non-monotonic assumptions consistent with background knowledge and action descriptions. Our intent is to demonstrate the connections between a general plan recognition model and important concepts of belief revision and non-monotonic reasoning, to help establish a basis for improving the specii-cation and development of specialized plan recognition systems.