This paper continues the investigation of the connection between probabilistically checkable proofs PCPs the approximability of NP-optimization problems. The emphasis is on prov...
This paper continues the investigation of the connection between probabilistically checkable proofs (PCPs) and the approximability of NP-optimization problems. The emphasis is on p...
We describe MarketSAT, a highly decentralized, marketbased algorithm for propositional satisfiability. The approach is based on a formulation of satisfiability as production on a ...
The surprisingly good performance of modern satisfiability (SAT) solvers is usually explained by the existence of a certain "hidden structure" in real-world instances. W...
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...