Fuzzy Constraint Satisfaction Using CCM — A Local Information Based Computation Model

The present paper proposes a method of solving the fuzzy constraint satisfaction problems defined by Ruttkay. This method is based on CCM, which is a computational 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 already 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 the evaluation functions are extended to real values, fuzzy CSPs can be expressed in CCM, and solved using a technique similar to GSAT or annealing. We applied this method to a fuzzy graph coloring problem, and evaluated the performance. This method can also be applied to open and dynamic fuzzy/non-fuzzy CSPs, in which data and constraints are changing dynamically or coming from or going to outside the system.