Acquiring Constraint Networks Using a SAT-based Version Space Algorithm

Acquiring Constraint Networks Using a SAT-based Version Space Algorithm
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使用基于 SAT 的版本空间算法获取约束网络

DOI:
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发表时间:
2006
期刊:
AAAI Conference on Artificial Intelligence
影响因子:
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通讯作者:
B. O’Sullivan
B. O’Sullivan
中科院分区:
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文献类型:
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作者:
C. Bessiere;Rémi Coletta;F. Koriche;B. O’Sullivan

文献摘要

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约束程序设计是解决复杂组合问题的一种常用技术。然而,这项技术的用户需要大量的专业知识,以便适当地模拟他们的问题。我们提出了一个解决这个问题的基础:一个新的基于SAT的版本空间算法,用于从目标问题的解决方案和非解决方案的例子中获取约束网络。该算法的一个重要优点是易于利用特定领域的知识。
Constraint programming is a commonly used technology for solving complex combinatorial problems. However, users of this technology need significant expertise in order to model their problems appropriately. We propose a basis for addressing this problem: a new SAT-based version space algorithm for acquiring constraint networks from examples of solutions and non-solutions of a target problem. An important advantage of the algorithm is the ease with which domain-specific knowledge can be exploited.