Phase 2: Enhanced Structural Barriers Analysis in SAT Solving with AI-Guided Algorithmic Improvements
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| Natura: | Recurso digital |
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Zenodo
2025
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| _version_ | 1866901041546526720 |
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| author | Ednyashev, Sanal |
| author_facet | Ednyashev, Sanal |
| contents | <p>This research demonstrates fundamental limitations in structural SAT analysis through AI-guided algorithm development. Key findings: 55.2% performance gap between semantic simulation (88.5% accuracy) and structural methods (33.3-55.2%). Includes working code, comprehensive benchmark of 96 instances, and reproducible analysis pipeline. Represents pioneering AI-human collaboration in computational complexity research with practical applications for SAT solver optimization.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15644659 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Phase 2: Enhanced Structural Barriers Analysis in SAT Solving with AI-Guided Algorithmic Improvements Ednyashev, Sanal <p>This research demonstrates fundamental limitations in structural SAT analysis through AI-guided algorithm development. Key findings: 55.2% performance gap between semantic simulation (88.5% accuracy) and structural methods (33.3-55.2%). Includes working code, comprehensive benchmark of 96 instances, and reproducible analysis pipeline. Represents pioneering AI-human collaboration in computational complexity research with practical applications for SAT solver optimization.</p> |
| title | Phase 2: Enhanced Structural Barriers Analysis in SAT Solving with AI-Guided Algorithmic Improvements |
| url | https://doi.org/10.5281/zenodo.15644659 |