The problem of deciding whether a propositional formula is satisfiable (SAT) is one of the most fundamental problems in computer science, both theoretically and practically. Due to its practical implications, intensive research has been performed on how to solve SAT problems in an automated fashion, and SAT solving is now a ubiquitous tool to solve many hard problems, both from industry and mathematics.
There are many generalizations of the SAT problem to further logics, including quantified Boolean formulas (QBFs), modal logics, and temporal logics. These logics present even harder satisfiability problems as they are associated with complexity classes such as PSPACE, which encompasses NP. Nevertheless, the last decade has seen the development of practically efficient algorithms for QBFs, SAT modulo theories (SMT), and further logics and their implementation as solvers, which successfully solve huge industrial instances. Since QBFs, SMT, modal logics, and temporal logics can express many practically relevant problems far more succinctly, they apply to even more real-world problems from artificial intelligence, bioinformatics, verification, and planning.
SAT is also increasingly being applied in logics that are not decidable, particularly in the context of first-order theorem proving. Here, fast SAT solvers are used for reasoning sub-tasks and for guiding the theorem provers.
The main aim of this Dagstuhl Seminar is to bring together researchers from different areas of activity on SAT and researchers that work in the field of first-order theorem proving so that they can communicate state-of-the-art advances and embark on a systematic interaction that will enhance the synergy between the different areas.
- Artificial Intelligence
- Computational Complexity
- Logic in Computer Science
- satisfiability problems
- computational and proof complexity
- first-order logic
- solvers for satisfiability problems
- non-classical logics