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AC-3d an Efficient Arc-Consistency Algorithm with a Low Space-Complexity

机译:AC-3D具有低空间复杂度的有效弧形一致性算法

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Arc-consistency algorithms prune the search-space of Constraint Satisfaction Problems (CSPs). They use support-checks to find out about the properties of CSPs. Their arc-heuristics select the constraint and their domain-heuristics select the values for the next support-check. We shall combine AC-3 and DEE and equip the resulting hybrid with a double-support domain-heuristic. The resulting hybrid AC-3d is easy to implement and requires the same data structures as AC-3 thereby improving on AC-7's space-complexity. We shall present experimental results which indicate that AC-3 can compete with AC-7.
机译:ARC-一致性算法修剪约束满意度问题的搜索空间(CSP)。他们使用支持检查了解CSP的属性。它们的弧启发式学习选择约束和域 - 启发式学习选择下一个支持检查的值。我们将使用双支撑域 - 启发式将AC-3和Dee结合起来,并配备由此产生的杂种。由此产生的混合AC-3D易于实现,并且需要与AC-3相同的数据结构,从而改善了AC-7的空间复杂性。我们将提出实验结果表明AC-3可以与AC-7竞争。

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