Learning From your mistakes, or By thinking. St Andrews. … for constraint satisfaction problems. Why learn?. Improve performance stop making the same mistakes! Provide explanations why is there no solution? why can’t I have a chocolate tea pot? React to change

ByProofs from SAT Solvers. Yeting Ge ACSys NYU Nov 20 2007. SAT solvers and proofs. SAT problem and solvers Given a propositional logic formula, a SAT solver outputs sat or unsat Proofs from SAT solvers are needed A certificate to show the solver is correct

ByGRASP: A Search Algorithm for Propositional Satisfiability. Sat in a Nutshell. Given a Boolean formula, find a variable assignment such that the formula evaluates to 1, or prove that no such assignment exists. For n variable,s there are 2 n possible truth assignments to be checked.

ByProof translation and SMT LIB certification. Yeting Ge Clark Barrett SMT 2008 July 7 Princeton. SMT solvers are more complicated. CVC3 contains over 100,000 lines of code Are SMT solvers correct?. Quest for correct SMT solvers?. To verify a SMT solver is correct?

ByA General Nogood -Learning Framework for Pseudo-Boolean Multi-Valued SAT* Siddhartha Jain Brown University Ashish Sabharwal IBM Watson Meinolf Sellmann IBM Watson * to appear at AAAI-2011. SAT and CSP/CP Solvers [complete search]. CP Solvers :

ByInterpolants from Z3 proofs. Ken McMillan Microsoft Research. TexPoint fonts used in EMF: A A A A A. Interpolating Z3. Deriving Craig interpolants from proofs (feasible interpolation) has a variety of applications in verification: Abstraction refinement

BySat solving maximization and minimization problems. Student: Victoria Kravchenko Supervisors: Prof. Yoram Moses Liat Atsmon. The Project Goal Study and evaluate the approach of solving optimization problems through SAT reduction, and using SAT solvers to solve the reduced problems.

ByA signment. tack. SAT’10 Conference Edinburgh, Scotland, UK July 11, 2010 . hrinking. Alexander Nadel, Intel, Israel Vadim Ryvchin, Intel&Technion , Israel. Agenda. Introduction Algorithm Description Heuristics Experimental Results Conclusions. What is Shrinking?.

ByBoolean Satisfiability Present and Future. Lintao Zhang Microsoft Research SVC. SAT: Introduction . Deciding the satisfiability of Boolean formulas SAT: Propositional ( usually in Conjunctive Normal Form (CNF) ) QBF: With quantifiers Many driving forces Verification

ByRelaxed DPLL Search for MaxSAT (short paper). Lukas Kroc, Ashish Sabharwal , Bart Selman Cornell University SAT-09 Conference Swansea, U.K. July 3, 2009. SAT and MaxSAT. SAT : Given a Boolean formula such as find, if possible, a truth assignment such that F is satisfied.

ByAn Efficient SMT Solver . Lecturer: Qinsi Wang May 2, 2012. Z3. high-performance theorem prover being developed at Microsoft Research. mainly by Leonardo de Moura and Nikolaj Bjørner . Free (online interface, APIs, …) but Not open source . Why Z3? .

ByNational Sun Yat-sen University Embedded System Laboratory. Finding Reset Nondeterminism in RTL Designs – Scalable X-Analysis Methodology and Case Study Cited count : 4 Hong- Zu Chou ; Haiqian Yu ; Kai- Hui Chang ; Dobbyn Dobbyn and Sy -Yen Kuo

ByProofs from SAT Solvers. Yeting Ge ACSys NYU Nov 20 2007. SAT solvers and proofs. SAT problem and solvers Given a propositional logic formula, a SAT solver outputs sat or unsat Proofs from SAT solvers are needed A certificate to show the solver is correct

By[published at AAAI-2013]. Resolution and Parallelizability: Barriers to the Efficient Parallelization of SAT Solvers George Katsirelos MIAT, INRA, Toulouse, France Ashish Sabharwal IBM Watson, USA Horst Samulowitz IBM Watson, USA Laurent Simon Univ. Paris- Sud , LRI/CNRS, Orsay , France.

ByHeavy-Tailed Phenomena in Satisfiability and Constraint Satisfaction Problems by Carla P. Gomes, Bart Selman, Nuno Crato and henry Kautz. Presented by Yunho Kim Provable Software Lab, KAIST. Introduction Search procedures and problem domains Cost distributions of backtrack search

ByLecture 21 State-Space Search vs. Constraint-Based Planning. CSE 573 Artificial Intelligence I Henry Kautz Fall 2001. Road Map. Today Plan graphs Planning as state space search Comparison of the two approaches. Graphplan. Planning as graph search (Blum & Furst 1995)

ByWorkshop on the Verification Grand Challenge. Panagiotis (Pete) Manolios Georgia Institute of Technology. Challenge: A Verified Microprocessor. International Technology Roadmap for Semiconductors, 2003 Edition

ByTime-Space Tradeoffs in Resolution: Lower Bounds for Superlinear Space. Chris Beck Princeton University Joint work with Paul Beame & Russell Impagliazzo. Resolution. Lines are clauses, one simple proof step Three basic flavors: Tree-like , Regular , and General Resolution.

ByKnowledge Compilation. Jinbo Huang NICTA and ANU. S l ides made by Adnan Darwiche and Jinbo Huang. B. C. A. Y. X. A okX B A okX B B okY C B okY C. KB =. Propositional Logic. Is A, C a normal device behavior?. A okX B

ByDLL Algorithm. How to realize search in hardware. We need to realize hardware stack Tree search is organized with hardware stack. The node of the tree is variable. The item on the stack is a sum of three literals (in 3SAT, can be more in general POS SAT).

ByView Sat solvers PowerPoint (PPT) presentations online in SlideServe. SlideServe has a very huge collection of Sat solvers PowerPoint presentations. You can view or download Sat solvers presentations for your school assignment or business presentation. Browse for the presentations on every topic that you want.