Advanced SMT techniques for weighted model integration

DOI10.1016/j.artint.2019.04.003zbMath1478.68328OpenAlexW2937129136WikidataQ128057624 ScholiaQ128057624MaRDI QIDQ2321319

Roberto Sebastiani, Paolo Morettin, Andrea Passerini

Publication date: 28 August 2019

Published in: Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.artint.2019.04.003

zbMATH Keywords

probabilistic inferencesatisfiability modulo theoriesweighted model countingweighted model integration

Mathematics Subject Classification ID

Reasoning under uncertainty in the context of artificial intelligence (68T37) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Related Items (3)

Unnamed Item ⋮ A compositional approach to probabilistic knowledge compilation ⋮ Approximate weighted model integration on DNF structures

Uses Software

• LattE
• MathSAT
• Dsharp

Cites Work

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• Inference in hybrid Bayesian networks using mixtures of polynomials
• Efficient solutions to factored MDPs with imprecise transition probabilities
• Approximate counting in SMT and value estimation for probabilistic programs
• Importance sampling-based estimation over AND/OR search spaces for graphical models
• Uniform generation of NP-witnesses using an NP-oracle
• Software for exact integration of polynomials over polyhedra
• Weighted model counting without parameter variables
• On probabilistic inference by weighted model counting
• How to integrate a polynomial over a simplex
• Probabilistic Databases
• Inference and learning in probabilistic logic programs using weighted Boolean formulas
• The MathSAT5 SMT Solver
• Compiling Probabilistic Graphical Models Using Sentential Decision Diagrams

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