On-Demand Bound Computation for Best-First Constraint Optimization (2004)  (Make Corrections)  (1 citation)
Martin Sachenbacher, Brian C. Williams

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Abstract: Many problems in Artificial Intelligence, such as diagnosis, control, and planning, can be framed as constraint optimization problems where a limited number of leading solutions are needed. An important class of optimization algorithms use A*, a variant of best first search, to guide the search e#ectively, while employing a heuristic evaluation function that is computed using dynamic programming. A key bottleneck, however, is that significant e#ort can be wasted precomputing bounds that... (Update)

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Diagnosis as Semiring-based Constraint Optimization - Sachenbacher, Williams (2004)   (Correct)

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BibTeX entry:   (Update)

Martin Sachenbacher and Brian Williams, `On-demand bound computation for best-first constraint optimization'. Submitted to CP-2004. http://citeseer.comp.nus.edu.sg/711904.html   More

@misc{ sachenbacher04demand,
  author = "M. Sachenbacher and B. Williams",
  title = "demand bound computation for best-first constraint optimization",
  text = "Martin Sachenbacher and Brian Williams, `On-demand bound computation for
    best-first constraint optimization'. Submitted to CP-2004.",
  year = "2004",
  url = "citeseer.comp.nus.edu.sg/711904.html" }
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42   Generalized Best-First Search Strategies and the Optimality (context) - Dechter, Pearl - 1985
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19   Focusing on Probable Diagnoses (context) - de Kleer - 1991
15   Topological methods in cardinal utility theory (context) - Debreu - 1959
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12   Distributed Databases (context) - Ceri, Pelagatti - 1984
10   A General Scheme for Automatic Generation of Search Heuristi.. - Kask, Dechter - 2001
9   A General Scheme for Multiple Lower Bound Computation in Con.. - Dechter, Kask et al. - 2001
7   Unifying Tree-Decomposition Schemes for Automated Reasoning - Kask - 2001
2   and its Role in Model-based Embedded Systems (context) - Williams, Ragno et al.

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