Boolean Propagation Based on Literals for Quantified Boolean Formulae

Watching Clauses in Quantified Boolean Formulae

The introduction of watched literals[1], a lazy data structure for satisfiability (SAT) search algorithms, has resulted in great improvements in the run-time of SAT solvers. Watched literals keeps track of two literals remaining in a clause so as to detect when a clause becomes unit or empty. Watched literals is non-trivial to implement in QBF search. Quantified Boolean Formulae (QBFs) are SAT ...

Solving 2-CNF Quantified Boolean Formulae Using Variable Assignment and Propagation

Monotone Literals and Learning in QBF Reasoning

Monotone literal fixing (MLF) and learning are well-known lookahead and lookback mechanisms in propositional satisfiability (SAT) . When considering Quantified Boolean Formulas (QBFs), their separate implementation leads to significant speed-ups in state-of-the-art DPLL-based solvers. This paper is dedicated to the efficient implementation of MLF in a QBF solver with learning. The interaction b...

Propagation Models and Fitting Them for the Boolean Random Sets

In order to study the relationship between random Boolean sets and some explanatory variables, this paper introduces a Propagation model. This model can be applied when corresponding Poisson process of the Boolean model is related to explanatory variables and the random grains are not affected by these variables. An approximation for the likelihood is used to find pseudo-maximum likelihood esti...

Backjumping for Quantified Boolean Logic Satisfiability

The implementation of effective reasoning tools for deciding the satisfiability of Quantified Boolean Formulas (QBFs) is an important research issue in Artificial Intelligence. Many decision procedures have been proposed in the last few years, most of them based on the Davis, Logemann, Loveland procedure (DLL) for propositional satisfiability (SAT). In this paper we show how it is possible to e...