A Structure-preserving Clause Form Translation
Journal of Symbolic Computation
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
DAC '96 Proceedings of the 33rd annual Design Automation Conference
GRASP—a new search algorithm for satisfiability
Proceedings of the 1996 IEEE/ACM international conference on Computer-aided design
A linear-time transformation of linear inequalities into conjunctive normal form
Information Processing Letters
Prioritized logic programming and its application to commonsense reasoning
Artificial Intelligence
A machine program for theorem-proving
Communications of the ACM
Chaff: engineering an efficient SAT solver
Proceedings of the 38th annual Design Automation Conference
Symbolic Model Checking
Symbolic Model Checking without BDDs
TACAS '99 Proceedings of the 5th International Conference on Tools and Algorithms for Construction and Analysis of Systems
Applying SAT Methods in Unbounded Symbolic Model Checking
CAV '02 Proceedings of the 14th International Conference on Computer Aided Verification
Generic ILP versus specialized 0-1 ILP: an update
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
The Complexity of Resolution Refinements
LICS '03 Proceedings of the 18th Annual IEEE Symposium on Logic in Computer Science
Comparing Arguments Using Preference Orderings for Argument-Based Reasoning
ICTAI '96 Proceedings of the 8th International Conference on Tools with Artificial Intelligence
Prime Implicant Computation Using Satisfiability Algorithms
ICTAI '97 Proceedings of the 9th International Conference on Tools with Artificial Intelligence
Pueblo: A Modern Pseudo-Boolean SAT Solver
Proceedings of the conference on Design, Automation and Test in Europe - Volume 2
Prime clauses for fast enumeration of satisfying assignments to boolean circuits
Proceedings of the 42nd annual Design Automation Conference
MaxSolver: an efficient exact algorithm for (weighted) maximum satisfiability
Artificial Intelligence
Unrestricted vs restricted cut in a tableau method for Boolean circuits
Annals of Mathematics and Artificial Intelligence
Preferred answer sets for ordered logic programs
Theory and Practice of Logic Programming
Algorithms for Computing Minimal Unsatisfiable Subsets of Constraints
Journal of Automated Reasoning
Logic programming with satisfiability
Theory and Practice of Logic Programming
Algorithms for maximum satisfiability using unsatisfiable cores
Proceedings of the conference on Design, automation and test in Europe
Computing All Optimal Solutions in Satisfiability Problems with Preferences
CP '08 Proceedings of the 14th international conference on Principles and Practice of Constraint Programming
Solving Optimization Problems with DLL
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Algorithms for Weighted Boolean Optimization
SAT '09 Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing
Constraint-based preferential optimization
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Planning as satisfiability with preferences
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Journal of Artificial Intelligence Research
New inference rules for Max-SAT
Journal of Artificial Intelligence Research
MINIMAXSAT: an efficient weighted max-SAT solver
Journal of Artificial Intelligence Research
In the quest of the best form of local consistency for weighted CSP
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Structural relaxations by variable renaming and their compilation for solving MinCostSAT
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
Clause form conversions for boolean circuits
SAT'04 Proceedings of the 7th international conference on Theory and Applications of Satisfiability Testing
Fifty-five solvers in vancouver: the SAT 2004 competition
SAT'04 Proceedings of the 7th international conference on Theory and Applications of Satisfiability Testing
Effective preprocessing in SAT through variable and clause elimination
SAT'05 Proceedings of the 8th international conference on Theory and Applications of Satisfiability Testing
Counterexample guided abstraction refinement algorithm for propositional circumscription
JELIA'10 Proceedings of the 12th European conference on Logics in artificial intelligence
Proceedings of the 2011 ACM Symposium on Applied Computing
Abstraction-based algorithm for 2QBF
SAT'11 Proceedings of the 14th international conference on Theory and application of satisfiability testing
Boolean lexicographic optimization: algorithms & applications
Annals of Mathematics and Artificial Intelligence
Managing dynamic CSPs with preferences
Applied Intelligence
On computing minimal correction subsets
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Propositional satisfiability (SAT) is a success story in Computer Science and Artificial Intelligence: SAT solvers are currently used to solve problems in many different application domains, including planning and formal verification. The main reason for this success is that modern SAT solvers can successfully deal with problems having millions of variables. All these solvers are based on the Davis---Logemann---Loveland procedure (dll). In its original version, dll is a decision procedure, but it can be very easily modified in order to return one or all assignments satisfying the input set of clauses, assuming at least one exists. However, in many cases it is not enough to compute assignments satisfying all the input clauses: Indeed, the returned assignments have also to be "optimal" in some sense, e.g., they have to satisfy as many other constraints--expressed as preferences--as possible. In this paper we start with qualitative preferences on literals, defined as a partially ordered set (poset) of literals. Such a poset induces a poset on total assignments and leads to the definition of optimal model for a formula 驴 as a minimal element of the poset on the models of 驴. We show (i) how dll can be extended in order to return one or all optimal models of 驴 (once converted in clauses and assuming 驴 is satisfiable), and (ii) how the same procedures can be used to compute optimal models wrt a qualitative preference on formulas and/or wrt a quantitative preference on literals or formulas. We implemented our ideas and we tested the resulting system on a variety of very challenging structured benchmarks. The results indicate that our implementation has comparable performances with other state-of-the-art systems, tailored for the specific problems we consider.