The potential synergy between instance-based pattern recognition and means-end (possible world) reasoning is explored, for supporting plan recognition in multi-aeroplane air-mission simulations. A means-end-reasoning model is then used to deliberate about and invoke standard operating procedures, based on recognized 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). The importance of capturing relative information in these multi-agents simulations is emphasized, including self-aeroplane, aeroplane-aeroplane and aeroplane-environment relationships.