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» Lazy Explanations for Constraint Propagators
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CPAIOR
2010
Springer
13 years 3 months ago
Lazy Clause Generation: Combining the Power of SAT and CP (and MIP?) Solving
Finite domain propagation solving, the basis of constraint programming (CP) solvers, allows building very high-level models of problems, and using highly specific inference encapsu...
Peter J. Stuckey
DAC
2006
ACM
14 years 6 months ago
Predicate learning and selective theory deduction for a difference logic solver
Design and verification of systems at the Register-Transfer (RT) or behavioral level require the ability to reason at higher levels of abstraction. Difference logic consists of an...
Chao Wang, Aarti Gupta, Malay K. Ganai
SAT
2007
Springer
121views Hardware» more  SAT 2007»
13 years 11 months ago
MiniMaxSat: A New Weighted Max-SAT Solver
In this paper we introduce MINIMAXSAT, a new Max-SAT solver that incorporates the best SAT and Max-SAT techniques. It can handle hard clauses (clauses of mandatory satisfaction as ...
Federico Heras, Javier Larrosa, Albert Oliveras
JAIR
2008
120views more  JAIR 2008»
13 years 5 months ago
MiniMaxSAT: An Efficient Weighted Max-SAT solver
In this paper we introduce MINIMAXSAT, a new Max-SAT solver that is built on top of MINISAT+. It incorporates the best current SAT and Max-SAT techniques. It can handle hard claus...
Federico Heras, Javier Larrosa, Albert Oliveras
IJCNN
2000
IEEE
13 years 9 months ago
Supervised Scaled Regression Clustering: An Alternative to Neural Networks
: This paper describes a rather novel method for the supervised training of regression systems that can be an alternative to feedforward Artificial Neural Networks (ANNs) trained w...
Mark J. Embrechts, Dirk Devogelaere, Marcel Rijcka...