Constraint Satisfaction Techniques for Combinatorial Problems

被引：0
|
作者：
Narvaez, David E. [1 ]
机构：
[1] Rochester Inst Technol, Golisano Coll Comp & Informat Sci, Rochester, NY 14623 USA
来源：
THIRTY-SECOND AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTIETH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / EIGHTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE | 2018年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The last two decades have seen extraordinary advances in industrial applications of constraint satisfaction techniques, while combinatorial problems have been pushed to the sidelines. We propose a comprehensive analysis of the state of the art in constraint satisfaction problems when applied to combinatorial problems in areas such as graph theory, set theory, algebra, among others. We believe such a study will provide us with a deeper understanding about the limitations we still face in constraint satisfaction problems.
引用
收藏
页码：8028 / 8029
页数：2
相关论文
共 50 条
  • [1] Structuring techniques for constraint satisfaction problems
    Weigel, R
    Faltings, BV
    [J]. IJCAI-97 - PROCEEDINGS OF THE FIFTEENTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOLS 1 AND 2, 1997, : 418 - 423
  • [2] Solution techniques for constraint satisfaction problems: Foundations
    Miguel, I
    Shen, Q
    [J]. ARTIFICIAL INTELLIGENCE REVIEW, 2001, 15 (04) : 243 - 267
  • [3] Solution Techniques for Constraint Satisfaction Problems: Foundations
    I. Miguel
    Q. Shen
    [J]. Artificial Intelligence Review, 2001, 15 : 243 - 267
  • [4] Solution Techniques for Constraint Satisfaction Problems: Advanced Approaches
    I. Miguel
    Q. Shen
    [J]. Artificial Intelligence Review, 2001, 15 : 269 - 293
  • [5] New structural decomposition techniques for constraint satisfaction problems
    Zheng, YL
    Choueiry, BY
    [J]. RECENT ADVANCES IN CONSTRAINTS, 2005, 3419 : 113 - 127
  • [6] DECOMPOSING CONSTRAINT SATISFACTION PROBLEMS USING DATABASE TECHNIQUES
    GYSSENS, M
    JEAVONS, PG
    COHEN, DA
    [J]. ARTIFICIAL INTELLIGENCE, 1994, 66 (01) : 57 - 89
  • [7] Solution techniques for constraint satisfaction problems: Advanced approaches
    Miguel, I
    Shen, Q
    [J]. ARTIFICIAL INTELLIGENCE REVIEW, 2001, 15 (04) : 269 - 293
  • [8] Combinatorial proof that subprojective constraint satisfaction problems are NP-complete
    Nesetril, Jaroslav
    Siggers, Mark
    [J]. MATHEMATICAL FOUNDATIONS OF COMPUTER SCIENCE 2007, PROCEEDINGS, 2007, 4708 : 159 - +
  • [9] Local Search Algorithms for Solving the Combinatorial Optimization and Constraint Satisfaction Problems
    Kilani, Y.
    Alsarhan, A.
    Bsoul, M.
    Otoom, A. F.
    [J]. SOFT COMPUTING APPLICATIONS, (SOFA 2014), VOL 1, 2016, 356 : 199 - 211
  • [10] Nature-Inspired Techniques for Dynamic Constraint Satisfaction Problems
    Bidar M.
    Mouhoub M.
    [J]. Operations Research Forum, 3 (2)
12345