Download PDFOpen PDF in browserCombining Conflict-Driven Clause Learning and Chronological Backtracking for Propositional Model Counting14 pages•Published: December 10, 2019AbstractIn propositional model counting, also named #SAT, the search space needs to be explored exhaustively, in contrast to SAT, where the task is to determine whether a propositional formula is satisfiable. While state-of-the-art SAT solvers are based on non- chronological backtracking, it has also been shown that backtracking chronologically does not significantly degrade solver performance. Hence investigating the combination of chronological backtracking with conflict-driven clause learning (CDCL) for #SAT seems evident. We present a calculus for #SAT combining chronological backtracking with CDCL and provide a formal proof of its correctness.Keyphrases: #sat, chronological backtracking, conflict driven clause learning, model counting, propositional calculus, rules, sat In: Diego Calvanese and Luca Iocchi (editors). GCAI 2019. Proceedings of the 5th Global Conference on Artificial Intelligence, vol 65, pages 113-126.
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