2002 | OriginalPaper | Buchkapitel
Learning and Solving Soft Temporal Constraints: An Experimental Study
verfasst von : Francesca Rossi, Alessandro Sperduti, Kristen B. Venable, Lina Khatib, Paul Morris, Robert Morris
Erschienen in: Principles and Practice of Constraint Programming - CP 2002
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
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Soft temporal constraints problems allow for a natural description of scenarios where events happen over time and preferences are associated with event distances and durations. However, sometimes such local preferences are difficult to set, and it may be easier instead to associate preferences to some complete solutions of the problem, and then to learn from them suitable preferences over distances and durations.In this paper, we describe our learning algorithm and we show its behaviour on classes of randomly generated problems. Moreover, we also describe two solvers (one more general and the other one more efficient) for tractable subclasses of soft temporal problems, and we give experimental results to compare them.