Introduction to algorithms
Artificial Intelligence - Special issue on knowledge representation
Remote Agent: to boldly go where no AI system has gone before
Artificial Intelligence - Special issue: artificial intelligence 40 years later
Fast transformation of temporal plans for efficient execution
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Temporal dynamic controllability revisited
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
Dynamic control of plans with temporal uncertainty
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Certainty closure: Reliable constraint reasoning with incomplete or erroneous data
ACM Transactions on Computational Logic (TOCL)
Controllability in Temporal Conceptual Workflow Schemata
BPM '09 Proceedings of the 7th International Conference on Business Process Management
On the partial observability of temporal uncertainty
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Modelling temporal, data-centric medical processes
Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
Drake: an efficient executive for temporal plans with choice
Journal of Artificial Intelligence Research
On the complexity of temporal controllabilities for workflow schemata
Proceedings of the 27th Annual ACM Symposium on Applied Computing
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An important issue for temporal planners is the ability to handle temporal uncertainty. Recent papers have addressed the question of how to tell whether a temporal network is Dynamically Controllable, i.e., whether the temporal requirements are feasible in the light of uncertain durations of some processes. Previous work has presented an O(N5) algorithm for testing this property. Here, we introduce a new analysis of temporal cycles that leads to an O(N4) algorithm.