A reactive approach for solving constraint satisfaction problems

被引:0
|
作者
Dury, A
Le Ber, F
Chevrier, V
机构
[1] LORIA, F-54506 Vandoeuvre Nancy, France
[2] INRA, LIAB, F-54280 Champenoux, France
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
We propose in this paper a multi-agent model for solving a class of Constraint Satisfaction Problems: the assignment problem. Our work is based on a real-world problem, the assignment of land-use categories in a farming territory, in the north-east of France. This problem exhibits a function to optimize, while respecting a set of constraints, both local (compatibility of grounds and land-use categories) and global (ratio of production between land-use categories). We developed a model using a purely reactive multi-agent system that builds its solution upon conflicts that arise during the resolution process. In this paper, we present the reactive modelling of the problem solving and experimental results from two points of view: the efficiency of the problem being solved and the properties of the problem solving process.
引用
收藏
页码:397 / 411
页数:15
相关论文
共 50 条
  • [1] A connectionist approach for solving large constraint satisfaction problems
    Likas, A
    Papageorgiou, G
    Stafylopatis, A
    [J]. APPLIED INTELLIGENCE, 1997, 7 (03) : 215 - 225
  • [2] An Incremental Approach to Solving Dynamic Constraint Satisfaction Problems
    Sharma, Anurag
    Sharma, Dharmendra
    [J]. NEURAL INFORMATION PROCESSING, ICONIP 2012, PT III, 2012, 7665 : 445 - 455
  • [3] A Connectionist Approach for Solving Large Constraint Satisfaction Problems
    A. Likas
    G. Papageorgiou
    A. Stafylopatis
    [J]. Applied Intelligence, 1997, 7 : 215 - 225
  • [4] Boolean approach for representing and solving constraint-satisfaction problems
    Bennaceur, H
    [J]. TOPICS IN ARTIFICIAL INTELLIGENCE, 1995, 992 : 163 - 174
  • [5] Neural networks approach for solving the Maximal Constraint Satisfaction Problems
    Ettaouil, Mohamed
    Haddouch, Khalid
    Hami, Youssef
    Loqman, Chakir
    [J]. 2013 8TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS: THEORIES AND APPLICATIONS (SITA), 2013,
  • [6] Solving fuzzy constraint satisfaction problems
    Meseguer, P
    Larrosa, J
    [J]. PROCEEDINGS OF THE SIXTH IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS I - III, 1997, : 1233 - 1238
  • [7] Solving quantified constraint satisfaction problems
    Gent, Ian P.
    Nightingale, Peter
    Rowley, Andrew
    Stergiou, Kostas
    [J]. ARTIFICIAL INTELLIGENCE, 2008, 172 (6-7) : 738 - 771
  • [8] Solving the Weighted Constraint Satisfaction Problems Via the Neural Network Approach
    Haddouch, Khalid
    Elmoutaoukil, Karim
    Ettaouil, Mohamed
    [J]. INTERNATIONAL JOURNAL OF INTERACTIVE MULTIMEDIA AND ARTIFICIAL INTELLIGENCE, 2016, 4 (01): : 56 - 60
  • [9] Solving constraint satisfaction and optimization problems by a neuro-fuzzy approach
    Cavalieri, S
    Russo, M
    [J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 1999, 29 (06): : 895 - 902
  • [10] Solving mixed and conditional constraint satisfaction problems
    Gelle, E
    Faltings, B
    [J]. CONSTRAINTS, 2003, 8 (02) : 107 - 141