Chapter 31. Quantified Boolean Formulas

Author:

Beyersdorff Olaf,Janota Mikoláš,Lonsing Florian,Seidl Martina

Abstract

Solvers for quantified Boolean formulas (QBF) have become powerful tools for tackling hard computational problems from various application domains, even beyond the scope of SAT. This chapter gives a description of the main algorithmic paradigms for QBF solving, including quantified conflict driven clause learning (QCDCL), expansion-based solving, dependency schemes, and QBF preprocessing. Particular emphasis is laid on the connections of these solving approaches to QBF proof systems: Q-Resolution and its variants in the case of QCDCL, expansion QBF resolution calculi for expansion-based solving, and QRAT for preprocessing. The chapter also surveys the relations between the various QBF proof systems and results on their proof complexity, thereby shedding light on the diverse performance characteristics of different solving approaches that are observed in practice.

Publisher

IOS Press

Cited by 18 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. QCDCL with cube learning or pure literal elimination – What is best?;Artificial Intelligence;2024-11

2. Counting QBF solutions at level two;Constraints;2024-08-08

3. Dependency Schemes in CDCL-Based QBF Solving: A Proof-Theoretic Study;Journal of Automated Reasoning;2024-07-24

4. Should Decisions in QCDCL Follow Prefix Order?;Journal of Automated Reasoning;2024-02-09

5. Quantifier Shifting for Quantified Boolean Formulas Revisited;Lecture Notes in Computer Science;2024

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