满意度搜索算法中的冲突分析

Joao Marques-Silva, K. Sakallah
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引用次数: 50

摘要

介绍了一种新的命题可满足性搜索算法GRASP (Generic seaRch Algorithm for Satisfiability Problem)。GRASP结合了几种搜索修剪技术,其中一些是SAT特有的,而另一些则在其他人工智能领域找到了等效的技术。GRASP以搜索过程中冲突的必然性为前提,其最大的特点是通过强大的冲突分析程序增强了基本的回溯搜索。分析冲突以确定其原因使GRASP能够非按时间顺序回溯到搜索树中的较早级别,这可能会修剪大部分搜索空间。此外,通过“记录”冲突的原因,GRASP可以在以后的搜索中识别和预防类似冲突的发生。最后,直接记录导致冲突的因果链,使GRASP能够确定找到解决方案所必需的分配。从大量基准测试中获得的实验结果表明,将所提出的冲突分析技术应用于SAT算法对于大量具有代表性的SAT实例类是非常有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Conflict analysis in search algorithms for satisfiability
Introduces GRASP (Generic seaRch Algorithm for the Satisfiability Problem), a new search algorithm for propositional satisfiability (SAT). GRASP incorporates several search-pruning techniques, some of which are specific to SAT, whereas others find equivalent in other fields of artificial intelligence. GRASP is premised on the inevitability of conflicts during a search, and its most distinguishing feature is the augmentation of the basic backtracking search with a powerful conflict analysis procedure. Analyzing conflicts to determine their causes enables GRASP to backtrack non-chronologically to earlier levels in the search tree, potentially pruning large portions of the search space. In addition, by "recording" the causes of conflicts, GRASP can recognize and preempt the occurrence of similar conflicts later on in the search. Finally, straightforward bookkeeping of the causality chains leading up to conflicts allows GRASP to identify assignments that are necessary for a solution to be found. Experimental results obtained from a large number of benchmarks indicate that application of the proposed conflict analysis techniques to SAT algorithms can be extremely effective for a large number of representative classes of SAT instances.
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