| 摘要: |
| 约束满足问题广泛出现于人工智能领域.在问题求解过程中保持局部约束一致性以缩小问题搜索空间是十分必要的.过去研究者对约束一致性算法的研究仅着眼于改进单个约束关系的维护.该文立足于更高点,提出从求解层次、维护层次和约束层次优化约束一致性维护的原则及其相应策略,算法MAC-H和AC-I+进一步减少了约束一致性维护的总代价,并克服了原有算法空间复杂度大的缺点.文中以两个典型的约束满足问题：N-皇后问题和斑马难题为分析和测试的例子,证实了这些原则和策略的有效性. |
| 关键词: 约束一致性维护,约束检测,多层次原则. |
| DOI： |
| 分类号: |
| 基金项目:本文研究得到国家自然科学基金和中国科学技术大学青年基金资助. |
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| Multi-level Strategy for Maintaining Arc Consistency in Problem Solving and Its Implementation |
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HAN Jing,CHEN En-hong,CAI Qing-sheng
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| Abstract: |
| Constraint satisfaction problems occur widely in artificial intelligence. Hence, arc consistency techniques have been widely studied to simplify constraint networks before or during the search for solutions. To reduce the cost of maintenance, the researchers have focused their work on the improvement of maintaining a single arc consistency. In this paper, from a higher point of view, the authors try to propose some principles and the corresponding strategies of three levels, which are search level, maintenance level and arc level. In this way, MAC-Dynamic and AC-I+ are presented. The effectiveness of this approach is demonstrated experimentally on two typical benchmarks of CSPs: Zebra Puzzles and N-Queen Problem. |
| Key words: Arc consistency, constraint check, multi-level principle. |
