mlsanityData to 14 Oct 2026

Learning Heuristics for Quantified Boolean Formulas through Deep Reinforcement Learning

arXiv 1807.08058 ↗First posted 20 Jul 2018cs.LO cs.AI cs.LGcited by 15

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Abstract (arXiv)

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 main challenge is to find a representation of these formulas that lends itself to making predictions in a scalable way. For a family of challenging problems, we learned a heuristic that solves significantly more formulas compared to the existing handwritten heuristics.

Key facts. Cited by 15 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 Jul 2018.

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Citing papers per year: 2021: 9; 2022: 4; 2023: 1; 2024: 1.

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  1. 2022Autoformalization with Large Language Modelscited by 263
  2. 2021Proof Artifact Co-training for Theorem Proving with Language Modelscited by 132
  3. 2021LIME: Learning Inductive Bias for Primitives of Mathematical Reasoningcited by 46
  4. 2021TacticZero: Learning to Prove Theorems from Scratch with Deep Reinforcement Learningcited by 37
  5. 2022Augment with Care: Contrastive Learning for Combinatorial Problemscited by 22
  6. 2021Neural Circuit Synthesis from Specification Patternscited by 17
  7. 2022Simplifying Polylogarithms with Machine Learningcited by 15
  8. 2021Train on Small, Play the Large: Scaling Up Board Games with AlphaZero and GNNcited by 6
  9. 2021Generating Symbolic Reasoning Problems with Transformer GANscited by 5
  10. 2021Can Graph Neural Networks Learn to Solve MaxSAT Problem?cited by 5
  11. 2022UNSAT Solver Synthesis via Monte Carlo Forest Searchcited by 3
  12. 2021Pretrained Cost Model for Distributed Constraint Optimization Problemscited by 1
3 more
  1. 2023Unveiling the Limits of Learned Local Search Heuristics: Are You the Mightiest of the Meek?cited by 1
  2. 2024Learning Better Representations From Less Data For Propositional Satisfiabilitycited by 1
  3. 2021Learning Heuristics for Template-based CEGIS of Loop Invariants with Reinforcement Learningcited by 0