Gil Lederman — accepted AI-conference papers

2021

Learning Branching Heuristics for Propositional Model Counting

Pashootan Vaezipoor, Gil Lederman, Yuhuai Wu, Chris Maddison, Roger B Grosse, Sanjit A. Seshia +1

AAAI 2021technical

Propositional model counting, or #SAT, is the problem of computing the number of satisfying assignments of a Boolean formula. Many problems from different application areas, including many discrete probabilistic inference problems, can be translated into model counting problems to be solved by #SAT…

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2020

Learning Heuristics for Quantified Boolean Formulas through Reinforcement Learning

Gil Lederman, Markus Rabe, Sanjit Seshia, Edward A. Lee

ICLR 2020poster

We demonstrate how to learn efficient heuristics for automated reasoning algorithms for quantified Boolean formulas through deep reinforcement learning. We focus on a backtracking search algorithm, which can already solve formulas of impressive size - up to hundreds of thousands of variables. The ma…

Cited by 41 Source ↗Scholar ↗