Uncertainty in Artificial Intelligence
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Search for Choquet-optimal paths under uncertainty
Lucie Galand, Patrice Perny
Abstract:
Choquet expected utility (CEU) is one of the most sophisticated decision criteria used in decision theory under uncertainty. It provides a generalisation of expected utility enhancing both descriptive and prescriptive possibilities. In this paper, we investigate the use of CEU for path-planning under uncertainty with a special focus on robust solutions. We first recall the main features of the CEU model and introduce some examples showing its descriptive potential. Then we focus on the search for Choquet-optimal paths in multivalued implicit graphs where costs depend on different scenarios. After discussing complexity issues, we propose two different heuristic search algorithms to solve the problem. Finally, numerical experiments are reported, showing the practical efficiency of the proposed algorithms.
Keywords:
Pages: 125-132
PS Link:
PDF Link: /papers/07/p125-galand.pdf
BibTex:
@INPROCEEDINGS{Galand07,
AUTHOR = "Lucie Galand and Patrice Perny",
TITLE = "Search for Choquet-optimal paths under uncertainty",
BOOKTITLE = "Proceedings of the Twenty-Third Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-07)",
PUBLISHER = "AUAI Press",
ADDRESS = "Corvallis, Oregon",
YEAR = "2007",
PAGES = "125--132"
}


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