Resolving Over-constrained Probabilistic Temporal Problems through Chance Constraint Relaxation
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Williams_Resolving over.pdf
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Author(s)
Yu, Peng
Fang, Cheng
Williams, Brian Charles
Date Issued
January 2015
Journal
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15)
Publisher
Association for the Advancement of Artificial Intelligence
Citation
Yu, Peng, Cheng Fang, and Brian Williams. "Resolving Over-constrained Probabilistic Temporal Problems through Chance Constraint Relaxation." in Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15), January 25-30, 2015, Austin Texas, USA.
Version
Author's final manuscript
Abstract
When scheduling tasks for field-deployable systems, our solutions must be robust to the uncertainty inherent in the real world. Although human intuition is trusted to balance reward and risk, humans perform poorly in risk assessment at the scale and complexity of real world problems. In this paper, we present a decision aid system that helps human operators diagnose the source of risk and manage uncertainty in temporal problems. The core of the system is a conflict-directed relaxation algorithm, called Conflict-Directed Chance-constraint Relaxation (CDCR), which specializes in resolving over-constrained temporal problems with probabilistic durations and a chance constraint bounding the risk of failure. Given a temporal problem with uncertain duration, CDCR proposes execution strategies that operate at acceptable risk levels and pinpoints the source of risk. If no such strategy can be found that meets the chance constraint, it can help humans to repair the over-constrained problem by trading off between desirability of solution and acceptable risk levels. The decision aid has been incorporated in a mission advisory system for assisting oceanographers to schedule activities in deep-sea expeditions, and demonstrated its effectiveness in scenarios with realistic uncertainty
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
http://www.aaai.org/Conferences/AAAI/2015/aaai15schedule.pdf
