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中文摘要：
约束满足问题在人工智能领域有着广泛的应用．研究了约束满足问题的粗粒度维持弧相容求解算法，发现在求解过程中，对于指向已赋值变量的弧存在无效的修正检查，证明了这类修正检查是冗余的．提出一种方法避免这类冗余的修正检查，给出改进后的粗粒度弧相容算法的基本框架AC3_frame_ARR，该改进框架可用于改进所有粗粒度弧相容算法．实验结果表明，经过AC3_flame_ARR改进后的算法最多可以节省80％的修正检查次数和40％的求解耗时．
英文摘要：
Constraint satisfaction problems have been widely investigated in artificial intelligence area. This paper investigates whether the coarse-grained maintaining arc is consistent, which is used to solve CSPs. The study has found that during the search for a solution, there are ineffective revisions, which revise the arcs that point to assigned variables. This study has proved that such revisions are redundant and proposed a method to avoid such redundant revisions. The paper gives the improved basic frame for the coarse-grained arc consistency algorithms, named AC3_frame_ARR. The new frame can be applied to improve all the coarse-grained AC algorithms. The exoerimental results show that the imoroved algorithms can save at most 80% revisions and 40% CPI time.
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