A New Probabilistic Algorithm for Approximate Model Counting

Constrained counting is important in domains ranging from artificial intelligence to software analysis. There are already a few approaches for counting models over various types of constraints. Recently, hashing-based approaches achieve both theoretical guarantees and scalability, but still rely on...

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Veröffentlicht in:	arXiv.org 2017-06
Hauptverfasser:	Ge, Cunjing, Ma, Feifei, Liu, Tian, Zhang, Jian
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial intelligence Constraint modelling Domains Empirical analysis Enumeration Polynomials
Online-Zugang:	Volltext
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