Uncertainty in Artificial Intelligence
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Dealing with Uncertainty in Situation Assessment: towards a Symbolic Approach
Charles Castel, Corine Cossart, Catherine Tessier
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.
Keywords: Symbolic uncertainty, reasoning under uncertainty, situation assessment.
Pages: 61-68
PS Link:
PDF Link: /papers/98/p61-castel.pdf
BibTex:
@INPROCEEDINGS{Castel98,
AUTHOR = "Charles Castel and Corine Cossart and Catherine Tessier",
TITLE = "Dealing with Uncertainty in Situation Assessment: towards a Symbolic Approach",
BOOKTITLE = "Proceedings of the Fourteenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-98)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1998",
PAGES = "61--68"
}


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