Projected Model Counting

July 28, 2015 Β· Declared Dead Β· πŸ› International Conference on Theory and Applications of Satisfiability Testing

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Authors Rehan Abdul Aziz, Geoffrey Chu, Christian Muise, Peter Stuckey arXiv ID 1507.07648 Category cs.AI: Artificial Intelligence Citations 58 Venue International Conference on Theory and Applications of Satisfiability Testing Last Checked 4 months ago
Abstract
Model counting is the task of computing the number of assignments to variables V that satisfy a given propositional theory F. Model counting is an essential tool in probabilistic reasoning. In this paper, we introduce the problem of model counting projected on a subset P of original variables that we call 'priority' variables. The task is to compute the number of assignments to P such that there exists an extension to 'non-priority' variables VΒΆthat satisfies F. Projected model counting arises when some parts of the model are irrelevant to the counts, in particular when we require additional variables to model the problem we are counting in SAT. We discuss three different approaches to projected model counting (two of which are novel), and compare their performance on different benchmark problems. To appear in 18th International Conference on Theory and Applications of Satisfiability Testing, September 24-27, 2015, Austin, Texas, USA
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