0871707322_Alloys
1 CSPs: Adding Structure to SAT George Katsirelos Fahiem Bacchus University of Toronto.
OUTLINE Boolean Equi-propagation for Optimized SAT Encoding Compiling Finite Domain Constraints to SAT with BEE Encoding process Design choices Compiling.
CP 2011
BIRS Workshop, Banff, Canada Jan 22, 2014 © 2014 IBM Corporation Resolution and Parallelizability: Barriers to the Efficient Parallelization of SAT Solvers.
Tradeoffs in Backdoors: Inconsistency Detection, Dynamic Simplification, and Preprocessing Bistra Dilkina, Carla Gomes, Ashish Sabharwal Cornell University.
Logical Foundations of AI SAT Henry Kautz. Resolution Refutation Proof DAG, where leaves are input clauses Internal nodes are resolvants Root is false.
SAT-solving An old AI technique becomes very popular in modern A.I.
Dynamic Restarts Optimal Randomized Restart Policies with Observation
Applications of Propositional Reasoning Systems
Methods for SAT- a Survey
[published at AAAI-2013]