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Generation and Prediction of Difficult Model Counting Instances

arXiv 2212.02893 ↗First posted 6 Dec 2022cs.AIcited by 0

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Abstract (arXiv)

We present a way to create small yet difficult model counting instances. Our generator is highly parameterizable: the number of variables of the instances it produces, as well as their number of clauses and the number of literals in each clause, can all be set to any value. Our instances have been tested on state of the art model counters, against other difficult model counting instances, in the Model Counting Competition. The smallest unsolved instances of the competition, both in terms of number of variables and number of clauses, were ours. We also observe a peak of difficulty when fixing the number of variables and varying the number of clauses, in both random instances and instances built by our generator. Using these results, we predict the parameter values for which the hardest to count instances will occur.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 3 of its 28 references that are in the map. First posted on arXiv 6 Dec 2022.

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References · 3

  1. 2020The Model Counting Competition 2020cited by 24
  2. 2014Stable Model Counting and Its Application in Probabilistic Logic Programmingcited by 8
  3. 2016Community Structure in Industrial SAT Instancescited by 4

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