This work reviews how database theory uses tractable circuit classes from knowledge
compilation. We present relevant query evaluation tasks, and notions of tractable circuits …

Answer set programming (ASP) is a popular declarative programming paradigm with a wide
range of applications in artificial intelligence. Oftentimes, when modeling an AI problem with …

Minimal models of a Boolean formula play a pivotal role in various reasoning tasks. While
previous research has primarily focused on qualitative analysis over minimal models; our …

Quantitative extensions of logic programming often require the solution of so called second
level inference tasks, that is, problems that involve a third operation, such as maximization or …

Although propositional model counting (# SAT) was long considered too hard to be practical,
today's highly efficient solvers facilitate applications in probabilistic reasoning, reliability …

Satisfiability Modulo Counting (SMC) encompasses problems that require both symbolic
decision-making and statistical reasoning. Its general formulation captures many real-world …

SharpSAT-TD is a recently published exact model counter that performed exceptionally well
in the recent editions of the Model Counting Competition (https://mccompetition. org/) …

The compilation of feature models into binary decision diagrams (BDDs) is a major
challenge in the area of configurable systems analysis. Many large-scale feature models …

The propositional model counting problem# SAT asks to compute the number of satisfying
assignments for a given propositional formula. Recently, three# SAT proof systems kcps …

Model counting is a fundamental problem in automated reasoning with applications in
probabilistic inference, network reliability, neural network verification, and more. Although …