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Symmetries in discrete constraint satisfaction problems have been explored and exploited in the last years, but symmetries in continuous constraint problems have not received the same attention. Here we focus on permutations of the variables consisting of one single cycle. We propose a procedure that takes advantage of these symmetries by interacting with a continuous constraint solver without interfering with it. A key concept in this procedure are the classes of symmetric boxes formed by bisecting a n-dimensional cube at the same point in all dimensions at the same time. We analyze these classes and quantify them as a function of the cube dimensionality. Moreover, we propose a simple algorithm to generate the representatives of all these classes for any number of variables at very high rates. A problem example from the chemical field and the cyclic n-roots problem are used to show the performance of the approach in practice.
FOS: Computer and information sciences, Computer Science - Artificial Intelligence, Continuous constraint satisfaction, Robotics, Constraint satisfaction, Symmetric boxes, Symmetry, Artificial Intelligence (cs.AI), Branch-and-prune, Robots
FOS: Computer and information sciences, Computer Science - Artificial Intelligence, Continuous constraint satisfaction, Robotics, Constraint satisfaction, Symmetric boxes, Symmetry, Artificial Intelligence (cs.AI), Branch-and-prune, Robots
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