Abstract Satisfiability Modulo Theories (SMT) refers to the problem of determining whether a
first-order formula is satisfiable with respect to some logical theory. Solvers based on SMT …

Constraint programming is a powerful paradigm for solving combinatorial search problems
that draws on a wide range of techniques from artificial intelligence, computer science …

Disjunctive Logic Programming (DLP) is an advanced formalism for knowledge
representation and reasoning, which is very expressive in a precise mathematical sense: it …

This article studies an implementation methodology for partial and disjunctive stable models
where partiality and disjunctions are unfolded from a logic program so that an …

Satisfiability problems and probabilistic models are core topics of artificial intelligence and
computer science. This paper looks at the rich intersection between these two areas …

Robustness and correctness are essential criteria for SAT and QBF solvers. We develop
automated testing and debugging techniques designed and optimized for SAT and QBF …

The high computational complexity of advanced reasoning tasks such as reasoning about
knowledge and planning calls for efficient and reliable algorithms for reasoning problems …

The n-Queens problem is to place n chess queens on an n by n chessboard so that no two
queens are on the same row, column or diagonal. The n-Queens Completion problem is a …

Deciding the satisfiability of a Quantified Boolean Formula (QBF) is an important research
issue in Artificial Intelligence. Many reasoning tasks involving planning [1], abduction …

We present a theorem-prover for quantified Boolean formulae and evaluate it on random
quantified formulae and formulae that represent problems from automated planning. Even …