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AAAI
2015

Resolving Over-Constrained Probabilistic Temporal Problems through Chance Constraint Relaxation

7 years 11 months ago
Resolving Over-Constrained Probabilistic Temporal Problems through Chance Constraint Relaxation
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 overconstrained 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 overconstrained problem by ...
Peng Yu, Cheng Fang, Brian Williams
Added 12 Apr 2016
Updated 12 Apr 2016
Type Journal
Year 2015
Where AAAI
Authors Peng Yu, Cheng Fang, Brian Williams
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