Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
Noise strategies for improving local search
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Experimental results on the crossover point in random 3-SAT
Artificial Intelligence - Special volume on frontiers in problem solving: phase transitions and complexity
Fast planning through planning graph analysis
Artificial Intelligence
Boosting combinatorial search through randomization
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Inferring state constraints for domain-independent planning
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
GRASP: A Search Algorithm for Propositional Satisfiability
IEEE Transactions on Computers
A machine program for theorem-proving
Communications of the ACM
Artificial Intelligence - special issue on computational tradeoffs under bounded resources
Chaff: engineering an efficient SAT solver
Proceedings of the 38th annual Design Automation Conference
Artificial Intelligence - Special issue on heuristic search in artificial intelligence
Heavy-Tailed Phenomena in Satisfiability and Constraint Satisfaction Problems
Journal of Automated Reasoning
Bounded Model Checking for Timed Systems
FORTE '02 Proceedings of the 22nd IFIP WG 6.1 International Conference Houston on Formal Techniques for Networked and Distributed Systems
Symbolic Model Checking without BDDs
TACAS '99 Proceedings of the 5th International Conference on Tools and Algorithms for Construction and Analysis of Systems
Planning via Model Checking: A Decision Procedure for AR
ECP '97 Proceedings of the 4th European Conference on Planning: Recent Advances in AI Planning
The complexity of theorem-proving procedures
STOC '71 Proceedings of the third annual ACM symposium on Theory of computing
Contingent planning under uncertainty via stochastic satisfiability
Artificial Intelligence - special issue on planning with uncertainty and incomplete information
Regression for Classical and Nondeterministic Planning
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Diagnosis of discrete-event systems using satisfiability algorithms
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Asymptotically optimal encodings of conformant planning in QBF
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
The FF planning system: fast plan generation through heuristic search
Journal of Artificial Intelligence Research
Towards understanding and harnessing the potential of clause learning
Journal of Artificial Intelligence Research
Constructing conditional plans by a theorem-prover
Journal of Artificial Intelligence Research
Heuristics based on unit propagation for satisfiability problems
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
Unifying SAT-based and graph-based planning
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Where the really hard problems are
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 1
Branching and pruning: An optimal temporal POCL planner based on constraint programming
Artificial Intelligence
Planning as satisfiability: parallel plans and algorithms for plan search
Artificial Intelligence
Verifying Industrial Hybrid Systems with MathSAT
Electronic Notes in Theoretical Computer Science (ENTCS)
A lightweight component caching scheme for satisfiability solvers
SAT'07 Proceedings of the 10th international conference on Theory and applications of satisfiability testing
Planning as satisfiability with relaxed ∃-step plans
AI'07 Proceedings of the 20th Australian joint conference on Advances in artificial intelligence
Pushing the envelope: planning, propositional logic, and stochastic search
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
AAAI'91 Proceedings of the ninth 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
Using CSP look-back techniques to solve real-world SAT instances
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
A robust and fast action selection mechanism for planning
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Heuristics for planning with SAT
CP'10 Proceedings of the 16th international conference on Principles and practice of constraint programming
The LAMA planner: guiding cost-based anytime planning with landmarks
Journal of Artificial Intelligence Research
Algorithm portfolio design: theory vs. practice
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
CADE' 20 Proceedings of the 20th international conference on Automated Deduction
Computing upper bounds on lengths of transition sequences
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Reduction to SAT is a very successful approach to solving hard combinatorial problems in Artificial Intelligence and computer science in general. Most commonly, problem instances reduced to SAT are solved with a general-purpose SAT solver. Although there is the obvious possibility of improving the SAT solving process with application-specific heuristics, this has rarely been done successfully. In this work we propose a planning-specific variable selection strategy for SAT solving. The strategy is based on generic principles about properties of plans, and its performance with standard planning benchmarks often substantially improves on generic variable selection heuristics, such as VSIDS, and often lifts it to the same level with other search methods such as explicit state-space search with heuristic search algorithms.