ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
Machine Learning
Fast planning through planning graph analysis
Artificial Intelligence
Chaff: engineering an efficient SAT solver
Proceedings of the 38th annual Design Automation Conference
Encoding Planning Problems in Nonmonotonic Logic Programs
ECP '97 Proceedings of the 4th European Conference on Planning: Recent Advances in AI Planning
SAT-based planning in complex domains: concurrency, constraints and nondeterminism
Artificial Intelligence - special issue on planning with uncertainty and incomplete information
Long-distance mutual exclusion for planning
Artificial Intelligence
Concise finite-domain representations for PDDL planning tasks
Artificial Intelligence
Extending SAT Solvers to Cryptographic Problems
SAT '09 Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing
Planning as satisfiability with preferences
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Fast planning by search in domain transition graph
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Explicit-state abstraction: a new method for generating heuristic functions
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Automatic SAT-compilation of planning problems
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
The FF planning system: fast plan generation through heuristic search
Journal of Artificial Intelligence Research
The fast downward planning system
Journal of Artificial Intelligence Research
Unifying SAT-based and graph-based planning
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
SAT encodings of state-space reachability problems in numeric domains
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Backdoors to typical case complexity
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Backbone guided local search for maximum satisfiability
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
A simplifier for propositional formulas with many binary clauses
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Planning as satisfiability: parallel plans and algorithms for plan search
Artificial Intelligence
Pushing the envelope: planning, propositional logic, and stochastic search
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
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Planning as satisfiability is a principal approach to planning with many eminent advantages. The existing planning as satisfiability techniques usually use encodings compiled from STRIPS. We introduce a novel SAT encoding scheme (SASE) based on the SAS+ formalism. The new scheme exploits the structural information in SAS+, resulting in an encoding that is both more compact and efficient for planning. We prove the correctness of the new encoding by establishing an isomorphism between the solution plans of SASE and that of STRIPS based encodings. We further analyze the transition variables newly introduced in SASE to explain why it accommodates modern SAT solving algorithms and improves performance. We give empirical statistical results to support our analysis. We also develop a number of techniques to further reduce the encoding size of SASE, and conduct experimental studies to show the strength of each individual technique. Finally, we report extensive experimental results to demonstrate significant improvements of SASE over the state-of-the-art STRIPS based encoding schemes in terms of both time and memory efficiency.