Title :
Learning for Dynamic Subsumption
Author :
Hamadi, Youssef ; Jabbour, Saïd ; Sais, Lakhdar
Author_Institution :
Microsoft Res., Cambridge, UK
Abstract :
This paper presents an original dynamic subsumption technique for Boolean CNF formulae. It exploits simple and sufficient conditions to detect, during conflict analysis, clauses from the formula that can be reduced by subsumption. During the learnt clause derivation, and at each step of the associated resolution process, checks for backward subsumption between the current resolvent and clauses from the original formula are efficiently performed. The resulting method allows the dynamic removal of literals from the original clauses. Experimental results show that the integration of our dynamic subsumption technique within the state-of-the-art SAT solvers Minisat and Rsat particularly benefits to crafted problems.
Keywords :
Boolean algebra; learning (artificial intelligence); Boolean CNF formulae; SAT solvers Minisat; associated resolution process; conflict analysis; dynamic subsumption; learnt clause derivation; Artificial intelligence; Boolean functions; Costs; Data preprocessing; Databases; Encoding; Learning; Lenses; Runtime; Sufficient conditions; Constraint Programming; Satisfiablity;
Conference_Titel :
Tools with Artificial Intelligence, 2009. ICTAI '09. 21st International Conference on
Conference_Location :
Newark, NJ
Print_ISBN :
978-1-4244-5619-2
Electronic_ISBN :
1082-3409
DOI :
10.1109/ICTAI.2009.22