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Title

A NEW METHOD FOR SOLVING CONSTRAINT SATISFACTION PROBLEMS

Pages

  1-14

Abstract

 Many Important problems In Artificial Intelligence can be defined as Constralnt Satisfaction Problems (CSP). These types of problems are defined by a limited set of variables, each having a limited domain and a number of Constralnts on the values of those variables (these problems are also called Consistent Labelling Problems (CLP), in which "Labeling" nuans assigning a value to a variable.) Solution to these problems is a set of unique values for variables such that all the problem constralnts are satisfied. Several SEARCH algorithms have been proposed for solving these problems, som of which reduce the need for bacJctracklng by doing some sort of looking to future, and produce more efficient solutions. These are the so-called Forward Checking (FC), Partialiy Lookahead (PL), and Fully Lookahead (FL) algorithms. They are different In terms of the amount of looking to the future, number of backtracks thaJ are performed, and the quality of the solution that they find. In this paper, wepropose a new SEARCH algorithm we call Modified Fully Lookahead (MFL) which is Shown to be more efficient than the original Fully Lookahead algorithm

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    APA: Copy

    GHASEM SANI, GH.R., & NAMAZI, M.. (2004). A NEW METHOD FOR SOLVING CONSTRAINT SATISFACTION PROBLEMS. ESTEGHLAL, 23(1), 1-14. SID. https://sid.ir/paper/5993/en

    Vancouver: Copy

    GHASEM SANI GH.R., NAMAZI M.. A NEW METHOD FOR SOLVING CONSTRAINT SATISFACTION PROBLEMS. ESTEGHLAL[Internet]. 2004;23(1):1-14. Available from: https://sid.ir/paper/5993/en

    IEEE: Copy

    GH.R. GHASEM SANI, and M. NAMAZI, “A NEW METHOD FOR SOLVING CONSTRAINT SATISFACTION PROBLEMS,” ESTEGHLAL, vol. 23, no. 1, pp. 1–14, 2004, [Online]. Available: https://sid.ir/paper/5993/en

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