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Artificial Intelligence
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In many AI fields, the problem of finding out a solution which is as close as possible to a given configuration has to be faced. This paper addresses this problem in a propositional framework. The decision problem DISTANCE-SAT that consists in determining whether a propositional CNF formula admits a model that disagrees with a given partial interpretation on at most d variables, is introduced. The complexity of DISTANCE-SAT an d of several restrictions of it are identified. Two algorithms based on the well-known Davis/Putnam search procedurea represented so as to solve DISTANCE-SAT. Their empirical evaluation enables deriving firm conclusionsa bout their respective performances and to relate the difficulty of DISTANCE-SAT with the difficulty of SAT from the practical side.