Graph Neural Networks for Reasoning 2-Quantified Boolean Formulas

no code implementations • 25 Sep 2019 • Fei Wang, Zhanfu Yang, Ziliang Chen, Guannan Wei, Tiark Rompf

In this paper, we target the QBF (Quantified Boolean Formula) satisfiability problem, the complexity of which is in-between propositional logic and predicate logic, and investigate the feasibility of learning GNN-based solvers and GNN-based heuristics for the cases with a universal-existential quantifier alternation (so-called 2QBF problems).

Logical Reasoning

Graph Neural Reasoning for 2-Quantified Boolean Formula Solvers

no code implementations • 27 Apr 2019 • Zhanfu Yang, Fei Wang, Ziliang Chen, Guannan Wei, Tiark Rompf

In this paper, we investigate the feasibility of learning GNN (Graph Neural Network) based solvers and GNN-based heuristics for specified QBF (Quantified Boolean Formula) problems.