On the greedy algorithm for satisfiability
Information Processing Letters
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
PSATO: a distributed propositional prover and its application to quasigroup problems
Journal of Symbolic Computation - Special issue on parallel symbolic computation
A threshold for unsatisfiability
Journal of Computer and System Sciences
Tail bounds for occupancy and the satisfiability threshold conjecture
Random Structures & Algorithms
Average case results for satisfiability algorithms under the random-clause-width model
Annals of Mathematics and Artificial Intelligence
Mick gets some (the odds are on his side) (satisfiability)
SFCS '92 Proceedings of the 33rd Annual Symposium on Foundations of Computer Science
Where the really hard problems are
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 1
Pushing the envelope: planning, propositional logic, and stochastic search
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Hard and easy distributions of SAT problems
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
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We consider the k-satisfiability problem. It is known that the random k-SAT model, in which the instance is a set of mk-clauses selected uniformly from the set of all k-clauses over n variables, has a phase transition at a certain clause density, below which most instances are satisfiable and above which most instances are unsatisfiable. The essential feature of the random k-SAT is that positive and negative literals occur with equal probability in a random formula. How does the phase transition behavior change as the relative probability of positive and negative literals changes? In this paper we focus on a distribution in which positive and negative literals occur with different probability. We present empirical evidence for the satisfiability phase transition for this distribution. We also prove an upper bound on the satisfiability threshold and a linear lower bound on the number of literals in satisfying partial assignments of skewed random k-SAT formulas.