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New hybrid SMT-NRA solver improves search efficiency

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a novel hybrid framework for Satisfiability Modulo the Theory of Nonlinear Real Arithmetic (SMT-NRA). This new approach integrates a 2D cell-jump move, which allows for broader search planes than existing methods, with an extended local search framework called 2D-LS. The system further incorporates MCSAT and OpenCAD, enabling efficient information exchange to enhance search performance. Experimental results indicate significant improvements in local search efficiency. AI

RANK_REASON The cluster contains an academic paper detailing a new computational method. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New hybrid SMT-NRA solver improves search efficiency

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The cluster contains an academic paper detailing a new computational method. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Tianyi Ding, Haokun Li, Xinpeng Ni, Bican Xia, Tianqi Zhao ·

    A Hybrid SMT-NRA Solver: Integrating 2D Cell-Jump-Based Local Search, MCSAT and OpenCAD

    arXiv:2507.00557v3 Announce Type: replace Abstract: In this paper, we propose a hybrid framework for Satisfiability Modulo the Theory of Nonlinear Real Arithmetic (SMT-NRA for short). First, we introduce a two-dimensional cell-jump move, called \emph{2D-cell-jump}, generalizing t…

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