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Meeting plan recognition requirements for real-time air-mission simulations

In this paper, the potential synergy between instancebased pattern recognition and means-end (possible world) reasoning is explored, for supporting plan recognition in multi-aeroplane air-mission simulations. A combination of graph matching, induction, probabilistic principles and dynamic programming are applied to traces of aeroplane behaviour during flight manoeuvres. These satisfy the real-time constraints of the simulation. This enables the agents to recognise what other agents are doing and to abstract about their activity, at the instrumentation level. A means-end-reasoning model is then used to deliberate about and invoke standard operating procedures, based on recognised activity. The reasoning model constrains the recognition process by framing queries according to what a pilot would expect during the execution of the current plan(s). Results from experiments involving the dMARS procedural reasoning system and the CLARET pattern matching and induction system are described for the BATTLEMODEL airmission simulator. The importance of capturing relative information in these multi-agent simulations is emphasised, including self-aeroplane, aeroplaneaeroplane and aeroplane-environment relationships.