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» Portfolio-based Parallel SAT solving
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ICDCS
2000
IEEE
14 years 2 months ago
The Effect of Nogood Learning in Distributed Constraint Satisfaction
We present resolvent-based learning as a new nogood learning method for a distributed constraint satisfaction algorithm. This method is based on a look-back technique in constrain...
Makoto Yokoo, Katsutoshi Hirayama
CADE
2006
Springer
14 years 10 months ago
Inferring Network Invariants Automatically
Abstract. Verification by network invariants is a heuristic to solve uniform verification of parameterized systems. Given a system P, a network invariant for P is that abstracts th...
Olga Grinchtein, Martin Leucker, Nir Piterman
DNA
2006
Springer
159views Bioinformatics» more  DNA 2006»
14 years 1 months ago
Minimal Parallelism for Polarizationless P Systems
Minimal parallelism was recently introduced [3] as a way the rules of a P system are used: from each set of applicable rules associated to the same membrane, at least one must be a...
Tseren-Onolt Ishdorj
JALC
2006
133views more  JALC 2006»
13 years 9 months ago
Power and Efficiency of Minimal Parallelism in Polarizationless P Systems
Minimal parallelism was recently introduced [3] as a way of using the rules of a P system: from each set of applicable rules associated to a membrane, at least one rule must be ap...
Tseren-Onolt Ishdorj
COCO
2005
Springer
123views Algorithms» more  COCO 2005»
14 years 3 months ago
If NP Languages are Hard on the Worst-Case Then It is Easy to Find Their Hard Instances
We prove that if NP ⊆ BPP, i.e., if SAT is worst-case hard, then for every probabilistic polynomial-time algorithm trying to decide SAT, there exists some polynomially samplable ...
Dan Gutfreund, Ronen Shaltiel, Amnon Ta-Shma