A mixed-integer linear programming problem which is efficiently solvable
Journal of Algorithms
Artificial Intelligence - Special issue on knowledge representation
Possibilistic constraint satisfaction problems or “how to handle soft constraints?”
UAI '92 Proceedings of the eighth conference on Uncertainty in Artificial Intelligence
Semiring-based constraint satisfaction and optimization
Journal of the ACM (JACM)
Issues in temporal reasoning for autonomous control systems
AGENTS '98 Proceedings of the second international conference on Autonomous agents
Deciding Linear Inequalities by Computing Loop Residues
Journal of the ACM (JACM)
Backtracking algorithms for disjunctions of temporal constraints
Artificial Intelligence
Communications of the ACM
A Probabilistic Approach to Robust Execution of Temporal Plans with Uncertainty
SETN '02 Proceedings of the Second Hellenic Conference on AI: Methods and Applications of Artificial Intelligence
Managing Temporal Uncertainty Through Waypoint Controllability
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Learning and Solving Soft Temporal Constraints: An Experimental Study
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Robust Temporal Constraint Network
ICTAI '05 Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence
Low-cost addition of preferences to DTPs and TCSPs
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Any time, complete algorithm for finding utilitarian optimal solutions to STPPs
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Temporal dynamic controllability revisited
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
Temporal reasoning with preferences and uncertainty
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Temporal constraint reasoning with preferences
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Dynamic control of plans with temporal uncertainty
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Disjunctive temporal planning with uncertainty
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Possibility theory for reasoning about uncertain soft constraints
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Fuzzy conditional temporal problems: Strong and weak consistency
Engineering Applications of Artificial Intelligence
RADAR: a personal assistant that learns to reduce email overload
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
A framework for reasoning under uncertainty with temporal constraints
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Drake: an efficient executive for temporal plans with choice
Journal of Artificial Intelligence Research
Computing all-pairs shortest paths by leveraging low treewidth
Journal of Artificial Intelligence Research
Distributed reasoning for multiagent simple temporal problems
Journal of Artificial Intelligence Research
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In real-life temporal scenarios, uncertainty and preferences are often essential and coexisting aspects. We present a formalism where quantitative temporal constraints with both preferences and uncertainty can be defined. We show how three classical notions of controllability (that is, strong, weak, and dynamic), which have been developed for uncertain temporal problems, can be generalized to handle preferences as well. After defining this general framework, we focus on problems where preferences follow the fuzzy approach, and with properties that assure tractability. For such problems, we propose algorithms to check the presence of the controllability properties. In particular, we show that in such a setting dealing simultaneously with preferences and uncertainty does not increase the complexity of controllability testing. We also develop a dynamic execution algorithm, of polynomial complexity, that produces temporal plans under uncertainty that are optimal with respect to fuzzy preferences.