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 realword 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.
Cite
Text
Castel et al. "Dealing with Uncertainty in Situation Assessment: Towards a Symbolic Approach." Conference on Uncertainty in Artificial Intelligence, 1998.Markdown
[Castel et al. "Dealing with Uncertainty in Situation Assessment: Towards a Symbolic Approach." Conference on Uncertainty in Artificial Intelligence, 1998.](https://mlanthology.org/uai/1998/castel1998uai-dealing/)BibTeX
@inproceedings{castel1998uai-dealing,
title = {{Dealing with Uncertainty in Situation Assessment: Towards a Symbolic Approach}},
author = {Castel, Charles and Cossart, Corine and Tessier, Catherine},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {1998},
pages = {61-68},
url = {https://mlanthology.org/uai/1998/castel1998uai-dealing/}
}