Weighted unranked tree automata as a framework for plan recognition

As the amount of information accessible to military intelligence continues to surge, operator assisted surveillance becomes less tractable. To process the information stream efficiently, automatic systems for threat detection are called for. These systems must be sufficiently robust to process incomplete or noisy data, and capable of dealing with uncertainties and probabilities. For safety reasons and accountability, it is imperative that the surveillance systems are specified in a formal framework that allows for rigorous mathematical verification. To this end, we demonstrate how the unobstructed keyhole plan recognition problem can be modelled within the framework of weighted unranked tree automata, and outline a software system for recognition of hostile behavior.