Generating Satisfiable Problem Instances
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
SAT graph-based representation: A new perspective
Journal of Algorithms
Generating Satisfiable SAT Instances Using Random Subgraph Isomorphism
Canadian AI '09 Proceedings of the 22nd Canadian Conference on Artificial Intelligence: Advances in Artificial Intelligence
Generating hard SAT/CSP instances using expander graphs
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
A simple model to generate hard satisfiable instances
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Notes on generating satisfiable SAT instances using random subgraph isomorphism
AI'10 Proceedings of the 23rd Canadian conference on Advances in Artificial Intelligence
On the resolution complexity of graph non-isomorphism
SAT'13 Proceedings of the 16th international conference on Theory and Applications of Satisfiability Testing
Automated reencoding of boolean formulas
HVC'12 Proceedings of the 8th international conference on Hardware and Software: verification and testing
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We introduce Satisfiable Random High Degree Subgraph Isomorphism Generator(SRHD-SGI), a variation of the Satisfiable Random Subgraph Isomorphism Generator (SR-SGI). We use the direct encoding to translate the SRHD-SGI instances into Satisfiable SAT instances. We present empirical evidence that the new model preserves the main characteristics of SAT encoded SR-SGI: easy-hard-easy pattern of evolution and exponential growth of empirical hardness. Our experiments indicate that SAT encoded SRHD-SGI instances are empirically harder than their SR-SGI counterparts. Therefore we conclude that SRHD-SGI is an improved generator of satisfiable SAT instances.