Abstract. Propositional satisfiability (SAT) is a success story in Computer Science and Artificial Intelligence: SAT solvers are currently used to solve problems in many different ...
Emanuele Di Rosa, Enrico Giunchiglia, Marco Marate...
In this paper, we propose a new approach, called lemma-reusing, for accelerating SAT based planning and scheduling. Generally, SAT based approaches generate a sequence of SAT prob...
Abstract. Work by Kilby, Slaney, Thiebaux and Walsh [1] showed that the backdoors and backbones of unstructured Random 3SAT instances are largely disjoint. In this work we extend t...
Propositional satisfiability (SAT) is a success story in Computer Science and Artificial Intelligence: SAT solvers are currently used to solve problems in many different applicati...
We present a faster method of solving optimal planning problems and show that our solution performs up to an order of magnitude faster than Satplan on a variety of problems from t...
Code optimization and high level synthesis can be posed as constraint satisfaction and optimization problems, such as graph coloring used in register allocation. Graph coloring is...
Arathi Ramani, Fadi A. Aloul, Igor L. Markov, Kare...
Recently spectacular improvements in the performance of SAT solvers have been achieved through nogood recording (clause learning). In the CSP literature, on the other hand, nogood ...
In recent years backtrack search SAT solvers have been the subject of dramatic improvements. These improvements allowed SAT solvers to successfully replace BDDs in many areas of f...
We define a collection of mappings that transform many-valued clausal forms into satisfiability equivalent Boolean clausal forms, analyze their complexity and evaluate them empir...
Advances in SAT solver technology have enabled many automated analysis and reasoning tools to reduce their input problem to a SAT problem, and then to use an efficient SAT solver ...