Leveraging Belief Propagation, Backtrack Search, and Statistics for Model Counting

DOI10.1007/978-3-540-68155-7_12zbMath1142.68517OpenAlexW2139937532MaRDI QIDQ5387627

Lukas Kroc, Ashish Sabharwal, Bart Selman

Publication date: 27 May 2008

Published in: Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-540-68155-7_12

Mathematics Subject Classification ID

Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Related Items

Exploiting symmetries for scaling loopy belief propagation and relational training ⋮ Projected model counting: beyond independent support ⋮ Performance of Sequential Local Algorithms for the Random NAE-$K$-SAT Problem ⋮ Learning cluster-based structure to solve constraint satisfaction problems ⋮ Leveraging belief propagation, backtrack search, and statistics for model counting

Uses Software

• MiniSat

Cites Work

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• On the hardness of approximate reasoning
• CCCP Algorithms to Minimize the Bethe and Kikuchi Free Energies: Convergent Alternatives to Belief Propagation
• A new look at survey propagation and its generalizations
• Constructing Free-Energy Approximations and Generalized Belief Propagation Algorithms
• Theory and Applications of Satisfiability Testing
• A Computing Procedure for Quantification Theory
• A machine program for theorem-proving
• Theory and Applications of Satisfiability Testing
• Characterizing Propagation Methods for Boolean Satisfiability
• Stochastic Boolean satisfiability

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