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MUSE CSP: An Extension to the Constraint Satisfaction Problem (1996) [1 citations — 1 self]

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@ARTICLE{Helzerman96musecsp:,
    author = {Randall A. Helzerman and Mary P. Harper},
    title = {MUSE CSP: An Extension to the Constraint Satisfaction Problem},
    journal = {Journal of Artificial Intelligence Research},
    year = {1996},
    volume = {5},
    pages = {5--239}
}

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Abstract:

This paper describes an extension to the constraint satisfaction problem (CSP) called MUSE CSP (MU ltiply SEgmented C onstraint Satisfaction Problem). This extension is especially useful for those problems which segment into multiple sets of partially shared variables. Such problems arise naturally in signal processing applications including computer vision, speech processing, and handwriting recognition. For these applications, it is often difficult to segment the data in only one way given the low-level information utilized by the segmentation algorithms. MUSE CSP can be used to compactly represent several similar instances of the constraint satisfaction problem. If multiple instances of a CSP have some common variables which have the same domains and constraints, then they can be combined into a single instance of a MUSE CSP, reducing the work required to apply the constraints. We introduce the concepts of MUSE node consistency, MUSE arc consistency, and MUSE path consistency. We th...

Citations

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