Disjoint Partial Enumeration without Blocking Clauses
Giuseppe Spallitta, Roberto Sebastiani, Armin Biere
摘要
A basic algorithm for enumerating disjoint propositional models (disjoint AllSAT) is based on adding blocking clauses incrementally, ruling out previously found models. On the one hand, blocking clauses have the potential to reduce the number of generated models exponentially, as they can handle partial models. On the other hand, the introduction of a large number of blocking clauses affects memory consumption and drastically slows down unit propagation. We propose a new approach that allows for enumerating disjoint partial models with no need for blocking clauses by integrating: Conflict-Driven Clause-Learning (CDCL), Chronological Backtracking (CB), and methods for shrinking models (Implicant Shrinking). Experiments clearly show the benefits of our novel approach.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper1
问问它们各自怎么用它它引用的顶会 Paper1
相关 Paper
- Guiding CDCL SAT Search via Random Exploration amid Conflict DepressionMd. Solimul Chowdhury, Martin Müller, Jia-Huai YouAAAI 2020 · 被引用 5 次
- Boolean Satisfiability via Imitation LearningZewei Zhang, Huan Liu, Yuanhao Yu, Jun Chen 等ICLR 2026
- Improving NLSAT for Nonlinear Real ArithmeticZhonghan WangASE 2025
- Runtime vs. Extracted Proof Size: An Exponential Gap for CDCL on QBFsOlaf Beyersdorff, Benjamin Böhm, Meena MahajanAAAI 2024 · 被引用 1 次
- A Cardinal Improvement to Pseudo-Boolean SolvingJan Elffers, Jakob NordströmAAAI 2020 · 被引用 9 次
