A New Model of Plan Recognition
  We present a new abductive, probabilistic theory of plan recognition. This
model differs from previous plan recognition theories in being centered around
a model of plan execution: most previous methods have been based on plans as
formal objects or on rules describing the recognition process. We show that our
new model accounts for phenomena omitted from most previous plan recognition
theories: notably the cumulative effect of a sequence of observations of
partially-ordered, interleaved plans and the effect of context on plan
adoption. The model also supports inferences about the evolution of plan
execution in situations where another agent intervenes in plan execution. This
facility provides support for using plan recognition to build systems that will
intelligently assist a user.
