Uncertainty in Artificial Intelligence
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Planning under Continuous Time and Resource Uncertainty: A Challenge for AI
John Bresina, Richard Dearden, Nicolas Meuleau, Sailesh Ramkrishnan, David Smith, Richard Washington
Abstract:
We outline a class of problems, typical of Mars rover operations, that are problematic for current methods of planning under uncertainty. The existing methods fail because they suffer from one or more of the following limitations: 1) they rely on very simple models of actions and time, 2) they assume that uncertainty is manifested in discrete action outcomes, 3) they are only practical for very small problems. For many real world problems, these assumptions fail to hold. In particular, when planning the activities for a Mars rover, none of the above assumptions is valid: 1) actions can be concurrent and have differing durations, 2) there is uncertainty concerning action durations and consumption of continuous resources like power, and 3) typical daily plans involve on the order of a hundred actions. This class of problems may be of particular interest to the UAI community because both classical and decision-theoretic planning techniques may be useful in solving it. We describe the rover problem, discuss previous work on planning under uncertainty, and present a detailed, but very small, example illustrating some of the difficulties of finding good plans.
Keywords:
Pages: 77-84
PS Link:
PDF Link: /papers/02/p77-bresina.pdf
BibTex:
@INPROCEEDINGS{Bresina02,
AUTHOR = "John Bresina and Richard Dearden and Nicolas Meuleau and Sailesh Ramkrishnan and David Smith and Richard Washington",
TITLE = "Planning under Continuous Time and Resource Uncertainty: A Challenge for AI",
BOOKTITLE = "Proceedings of the Eighteenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-02)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "2002",
PAGES = "77--84"
}


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