Handbook of Satisfiability: Volume 185 Frontiers in Artificial Intelligence and Applications

By Armin Biere, Marijn J. H. Heule, Hans van Maaren, Thomas J. Walsh. 2009

610 citations recorded by the source corpus.

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Citations in the corpus

Learning Optimal Decision Trees with MaxSAT and its Integration in AdaBoost (2020, methodology): “We give a brief background on (Maximum) Boolean Satis-ﬁablity and we refer the reader to [ Biere et al. , 2009 ] for a comprehensive reference.”
Abduction-Based Explanations for Machine Learning Models (2018, methodology): “We assume deﬁnitions standard in propositional logic and satiﬁability (Biere et al. 2009), with the usual deﬁnitions for (CNF) formulas, clauses and literals.”
Potassco: The Potsdam Answer Set Solving Collection (2011, unknown): “This approach is closely related to the one pursued in propositional Satisﬁability Testing (SAT; [9]), where problems are encoded as propositional theories whose models represent the solutions to the given problem.”
Verifying Properties of Binarized Deep Neural Networks (2017, methodology): “Otherwise, we generate an interpolant I of Gen( x + τ, y ) ∧ Ver( y = ˆ y , z , o, (cid:96) x ) by extracting an un-satisﬁable core of Ver( y = ˆ y , z , o, (cid:96) x ) (Biere et al. 2009).”
Core-Boosted Linear Search for Incomplete MaxSAT (2019, background): “The NP-complete Boolean Satisfiability problem (SAT) asks to decide if a given CNF formula F is satisfiable [17].”
Do-calculus when the True Graph Is Unknown (2015, methodology): “This enables the application of modern constraint solving techniques, such as Boolean satisfiability (SAT) solvers (Biere et al., 2009).”
Model-free, Model-based, and General Intelligence (2018, background): “…and stochastic planning problems (FONDPs, PONDPs, MDPs, and POMDPs), general game playing, and answer set programming among others [Dechter, 2003; Biere et al., 2009; Pearl, 1988; Geffner and Bonet, 2013; Bertsekas, 1995; Kaelbling et al., 1998; Genesereth et al., 2005; Gebser et al., 2012].”
Conflict-driven answer set solving: From theory to practice (2012, methodology): “To this end, it features a number of sophisticated reasoning and implementation techniques, some specific to ASP and others borrowed from CDCL-based SAT solvers.”
Techniques Inspired by Local Search for Incomplete MaxSAT and the Linear Algorithm: Varying Resolution and Solution-Guided Search (2019, methodology): “See [8] for more information on SAT and MaxSAT.”
Secure two-party computations in ANSI C (2012, methodology): “We will first describe the functionality of CBMC, and then explain our modifications.”
Constraint-based Causal Discovery: Conflict Resolution with Answer Set Programming (2014, methodology): “Constraint-based Causal Discovery: Conflict Resolution with Answer Set Programming Paper Supplement Antti Hyttinen and Frederick Eberhardt California Institute of Technology Pasadena, CA, USA Matti Järvisalo HIIT & Department of Computer Science University of Helsinki, Finland”