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,...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Association for the Advancement of Artificial Intelligence,
2015-01-20T16:58:42Z.
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| Subjects: | |
| Online Access: | Get fulltext |