A Novel Approach For Detecting Symmetries in CSP Models

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Abstract

While several powerful methods exist for automatically detecting symmetries in instances of constraint satisfaction problems (CSPs), current methods for detecting symmetries in CSP models are limited to the kind of symmetries that can be inferred from the global constraints present in the model. Herein, a new approach for detecting symmetries in CSP models is presented. The approach is based on first applying powerful methods to a sequence of problem instances, and then reasoning on the resulting instance symmetries to infer symmetries of the model. Our results show that this approach deserves further exploration.