电子学报 ›› 2020, Vol. 48 ›› Issue (5): 899-905.DOI: 10.3969/j.issn.0372-2112.2020.05.009

• 学术论文 • 上一篇    下一篇

基于IAPS的扩展规则局部搜索算法

王金艳1,2, 胡春2, 牛当当1,3, 李先贤1,2   

  1. 1. 广西多源信息挖掘与安全重点实验室(广西师范大学), 广西桂林 541004;
    2. 广西师范大学计算机科学与信息工程学院, 广西桂林 541004;
    3. 西北农林科技大学信息工程学院, 陕西杨凌 712100
  • 收稿日期:2019-11-15 修回日期:2020-02-10 出版日期:2020-05-25 发布日期:2020-05-25
  • 通讯作者: 李先贤
  • 作者简介:王金艳 女,1982年1月2日生,广西资源人.现为广西师范大学计算机科学与信息工程学院副教授,主要研究方向为自动推理和数据安全.E-mail:wangjy612@gxnu.edu.cn;胡春 男,1995年3月1日生,江西南昌人.现为广西师范大学计算机科学与信息工程学院研究生,主要研究方向为自动推理和人工智能.E-mail:huchungxnu@163.com;牛当当 男,1990年2月出生,陕西周至人.现为西北农林科技大学信息工程学院讲师,主要研究方向为自动推理和抽象论辩.E-mail:niudd@nwafu.edu.cn
  • 基金资助:
    国家自然科学基金(No.61763003,No.61672176,No.61941201);广西多源信息挖掘与安全重点实验室系统性研究课题基金(No.19-A-02-01);广西多源信息挖掘与安全重点实验室开放基金(No.MIMS19-05);广西高等学校千名中青年骨干教师培育计划;"八桂学者"工程专项经费资助项目;广西大数据智能与应用人才小高地;广西区域多源信息集成与智能处理协同创新中心

An Extension Rule Algorithm Based on Local Search with IAPS Strategies

WANG Jin-yan1,2, HU Chun2, NIU Dang-dang1,3, LI Xian-xian1,2   

  1. 1. Guangxi Key Lab of Multisource Information Mining&Security(Guangxi Normal University), Guilin, Guangxi 541004, China;
    2. School of Computer Science and Information Engineering, Guangxi Normal University, Guilin, Guangxi 541004, China;
    3. College of Information Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China
  • Received:2019-11-15 Revised:2020-02-10 Online:2020-05-25 Published:2020-05-25

摘要: ERACC(Extension Rule Based on Accurate Configuration Checking)算法由杨洋等人基于扩展规则和格局检测提出,具有较高的推理效率.为进一步提高ERACC算法在大规模SAT(Satisfiability)问题求解上的性能,本文在搜索由极大项组成的空间时,首先利用IMOM(Improved Maximum Occurrences on Clauses of Maximum Size)思想生成初始极大项,接着设计了适用于扩展规则推理的CCA_ER(Configuration Checking with Aspiration for Extension Rule-Based Reasoning)启发式策略,为极大项中格局信息未发生变化的变量对应文字提供一定的翻转机会.同时,为进一步提高扩展规则推理算法在k-SAT问题求解上的性能,设计了适用于扩展规则推理的PAWS_ER(Pure Additive Weighting Scheme for Extension Rule-Based Reasoning)策略,并且给出变量的Subscore_ER(Subscore for Extension Rule-Based Reasoning),CScore_ER(Comprehensive Score for Extension Rule-Based Reasoning)和HScore_ER(Hybrid Score for Extension Rule-Based Reasoning)属性.在此基础上,提出了ERACC_IAPS(ERACC with IMOM,CCA_ER,PAWS_ER and Subscore_ER)和CERACC_IAPS(ERACC with IMOM,CCA_ER,PAWS_ER,CScore_ER and HScore_ER)算法.实验结果表明:ERACC_IAPS和CERACC_IAPS算法的效率明显优于ERACC算法,最高可将其求解效率提高1000多倍.

关键词: 扩展规则, 自动推理, 局部搜索, 格局检测

Abstract: The algorithm ERACC proposed by Yang et al.has high reasoning efficiency.To further improve performance of ERACC algorithm in solving large-scale SAT problem,firstly,IMOM is used to generate the initial maximum term. Then a CCA_ER is designed to provide certain opportunities for the literals of variables whose configurations have not been changed since their last flips in maximal terms. At the same time,in order to further improve the performance of extension rule-based reasoning algorithm on the k-SAT problem,PAWS_ER is designed. Then the Subscore_ER,CScore_ER and HScore_ER attributes for variables are further designed. Finally,ERACC_IAPS and CERACC_ER algorithms are proposed. The experimental results show that the efficiency of ERACC_IAPS and CERACC_IAPS algorithms is obviously better than that of ERACC algorithm,and the maximum solution efficiency can be improved by more than 1000 times.

Key words: extension rule, automated reasoning, local search, configuration checking

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