Abstract
The fuzzy constraint satisfaction framework is a successful extension to the classical constraint satisfaction problem (CSP) framework which allows the representation of the softness often inherent in real problems. Examples include the expression of both relative constraint priorities and preferences amongst potential variable assignments. A second property common to many real problems is the likelihood of change to the problem structure over time. This aspect has already been addressed by the techniques of dynamic constraint satisfaction with respect to classical CSP. This paper presents a new algorithm, flexible local changes, capable of solving both static and dynamic fuzzy constraint satisfaction problems (FCSPs), hence maintaining the greater expressive power of fuzzy CSP in a dynamic environment. An illustrative example is provided and experimental testing is described with results.
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