Abstract
We study propagation of a global constraint that ensures that each row of a matrix of decision variables satisfies a Regular constraint, and each column satisfies a Gcc constraint. On the negative side, we prove that propagation is NP-hard even under some strong restrictions (e.g. just 2 values, just 4 states in the automaton, just 5 columns to the matrix, or restricting to limited classes of automata). We also prove that propagation is W[2]-hard when the problem is parameterized by the number of rows in the matrix. On the positive side, we identify several cases where propagation is fixed parameter tractable.
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de Haan, R., Narodytska, N., Walsh, T. (2012). The RegularGcc Matrix Constraint. In: Thielscher, M., Zhang, D. (eds) AI 2012: Advances in Artificial Intelligence. AI 2012. Lecture Notes in Computer Science(), vol 7691. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35101-3_18
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DOI: https://doi.org/10.1007/978-3-642-35101-3_18
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