Dealing with Uncertainty in Situation Assessment: towards a Symbolic Approach

Abstract

The situation assessment problem is considered, in terms of object, condition, activity, and plan recognition, based on data coming from the real-word {em via} various sensors. It is shown that uncertainty issues are linked both to the models and to the matching algorithm. Three different types of uncertainties are identified, and within each one, the numerical and the symbolic cases are distinguished. The emphasis is then put on purely symbolic uncertainties: it is shown that they can be dealt with within a purely symbolic framework resulting from a transposition of classical numerical estimation tools.