Fuzzy Constraint Satisfaction Using CCM -- A Local Information Based Computation Model
Kanada, K., Fuzz-IEEE/IFES '95, pp. 2319-2326, 1995.
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Abstract: A method of solving fuzzy constraint satisfaction problems defined by Ruttkay is shown in the present paper. This method is based on CCM, which is a computation model for emergent computation or for locality-based problem solving. CCM is a type of production system. It works stochastically, or randomly, and works with evaluation functions that are computed only with local information. CCM has been applied to constraint satisfaction problems (CSPs). Binary-valued evaluation functions, each of which indicates whether a constraint is satisfied, are used. If the values of evaluation functions are extended to real values, fuzzy CSPs can be expressed in CCM, and solved using a technique similar to GSAT or annealing. This method is applied to a fuzzy graph coloring problem, and the performance is evaluated. This method can also be applied to an open and dynamical fuzzy/non-fuzzy CSPs, in which data and constraints are changing dynamically or coming from or going to the outside of the system.
Introduction to this research theme: CCM: Chemical-Computation Model