*Carla P. Gomes, Bart Selman*

Recent progress on search and reasoning procedures has been driven by experimentation on computationally hard problem instances. Hard random problem distributions are an important source of such instances. Challenge problems from the area of finite algebra have also stimulated research on search and reasoning procedures. Nevertheless, the relation of such problems to practical applications is somewhat unclear. Realistic problem instances clearly have more structure than the random problem instances, but, on the other hand, they are not as regular as the structured mathematical problems. We propose a new benchmark domain that bridges the gap between the purely random instances and the highly structured problems, by introducing perturbations into a structured domain. We will show how to obtain interesting search problems in this manner, and how such problems can be used to study the robustness of search control mechanisms. Our experiments demonstrate that the performance of search strategies designed to mimic direct constructive methods degrade surprisingly quickly in the presence of even minor perturbations.

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