Instances of the futile questioning problem abound in applications, especially, in the area of artificial intelligence. The problem can be represented by a particular quantified Boolean formula. A variation of the problem includes also costs for the logic variables. Typically, the problem is simplified instead of solved directly, which may lead to inaccurate results. Alternatively, the problem ...

In this paper we present a new technique to solve Quantified Boolean Formulas (QBF). Our technique applies the idea of dynamic partitioning to QBF solvers. Dynamic partitioning has previously been utilized in #SAT solvers that count the number of models of a propositional formula. One of the main differences with the #SAT case comes from the solution learning techniques employed in search based...

In this paper we consider the problem of checking whether a partial implementation can (still) be extended to a complete design which is equivalent to a given full specification. In particular, we investigate the relationship between the equivalence checking problem for partial implementations (PEC) and the validity problem for quantified Boolean formulae (QBF) with so-called Henkin quantifiers...

Solvers for Quantified Boolean Formulae (QBF) use many analogues of technique from SAT. A significant amount of work has gone into extending conflict based techniques such as conflict learning to solution learning, which is irrelevant in SAT but can play a large role in success in QBF. Unfortunately, solution learning techniques have not been highly successful to date. We argue that one reason ...

A combinational circuit can be tested for the presence of a single stuck-at fault by applying a set of inputs that excite a verifiable output response in that circuit. If the fault is present, the output will be different than it would be if the fault were not present. Given a circuit, the goal of an automatic test pattern generation system is to generate a set of input sets that will detect ev...

Through minimal-model semantics, three-valued logics provide an interesting formalism for capturing reasoning from inconsistent information. However, the resulting paraconsistent logics lack so far a uniform implementation platform. Here, we address this and specifically provide a translation of two such paraconsistent logics into the language of quantified Boolean formulas (QBFs). These formul...

Learning, i.e., the ability to record and exploit some information which is unveiled during the search, proved to be a very effective AI technique for problem solving and, in particular, for constraint satisfaction. In (Giunchiglia et al. 2002) we have introduced learning as a general purpose technique to improve the performances of decision procedures for Quantified Boolean Formulas (QBFs). We...

In the past few years, we have seen significant progress in the area of Boolean satisfiability (SAT) solving and its applications. More recently, new efforts have focused on developing solvers for Quantified Boolean Formulas (QBFs). Recent QBF evaluation results show that developing practical QBF solvers is more challenging than one might expect. Even relatively small QBF problems are sometimes...

We study the complexity of some new probabilistic variant of the problem Quantified Satisfiability(QSAT). Let a sentence ∃v1∀v2 . . . ∃vn−1∀vnφ be given. In classical game associated with the QSAT problem, the players ∃ and ∀ alternately chose Boolean values of the variables v1, . . . , vn. In our game one (or both) players can instead determine the probability that vi is true. We call such pla...