Solving Dynamic CSPs

Abstract

Constraint Satisfaction problems (CSPs) are a fundamental concept used in many real world applications such as frequency assignment, configuration and conceptual design, scheduling and planning. A main challenge when designing a CSP-based system is the ability to deal with constraints in a dynamic and evolutive environment. During the conceptual phase of design, for example, the designers should be able to add/remove constraints at any time after specifying an initial statement describing the desired properties of a required artifact. We propose in this paper a new dynamic arc consistency algorithm that has a better compromise between time and space than those algorithms proposed in the literature, in addition to the simplicity of its implementation. Experimental tests on randomly generated CSPs demonstrate the efficiency of our algorithm to deal with large size problems in a dynamic environment.