Uncertainty in soft temporal constraint problems: A general framework and controllability algorithms for the fuzzy case

被引：0
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作者：
Rossi, Francesca [1 ]
Venable, Kristen Brent [1 ]
Yorke-Smith, N. [2 ]
机构：
[1] University of Padova, Department of Pure and Applied Mathematics, Via Trieste 63, 35121 Padova, Italy
[2] SRI International, 333 Ravenswood Ave, Menlo Park, CA 94025, United States
来源：
Journal of Artificial Intelligence Research | 2006年 / 27卷
关键词：
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. © 2006 AI Access Foundation. All rights reserved;
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页码：617 / 674
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