Megan Eskey

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Zweben, M., E. Davis, B. Daun, E. Drascher, M. Deale and M. Eskey, Learning to improve constraint-based scheduling, Artificial Intelligence 58 (1992) 271-296. This paper describes an application of an analytical learning technique, plausible explanation-based learning (PEBL), that dynamically acquires search control knowledge for a constraint-based(More)
This paper describes the design and implementation of a constraint satisfaction system that uses delayed evaluation techniques to provide greater representational power and to avoid unnecessary computation. The architecture used is a uniform model of computation, where each constraint contributes its local information to provide a global solution. We(More)
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