Learning for Dynamic subsumption
| dc.creator | Hamadi, Youssef | |
| dc.creator | Jabbour, Said | |
| dc.creator | Sais, Lakhdar | |
| dc.date | 2009-03-31 | |
| dc.date.accessioned | 2026-07-07T12:58:57Z | |
| dc.date.available | 2026-07-07T12:58:57Z | |
| dc.description | In this paper a new dynamic subsumption technique for Boolean CNF formulae is proposed. It exploits simple and sufficient conditions to detect during conflict analysis, clauses from the original formula that can be reduced by subsumption. During the learnt clause derivation, and at each step of the resolution process, we simply check for backward subsumption between the current resolvent and clauses from the original formula and encoded in the implication graph. Our approach give rise to a strong and dynamic simplification technique that exploits learning to eliminate literals from the original clauses. Experimental results show that the integration of our dynamic subsumption approach within the state-of-the-art SAT solvers Minisat and Rsat achieves interesting improvements particularly on crafted instances. | |
| dc.identifier | https://arxiv.org/abs/0904.0029 | |
| dc.identifier | http://arxiv.org/abs/0904.0029 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/225422 | |
| dc.subject | Artificial Intelligence | |
| dc.title | Learning for Dynamic subsumption | |
| dc.type | text |