Research map / Learning theory and algorithms / Combinatorial and search optimization
Probabilistic Generalization of Backdoor Trees with Application to SAT
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use a ρ-backdoor tree found by the proposed search instead of solving the original formula directly | SAT instances with Unit Propagation and Kissat · PvS7,4; BvP7,6; BvP8,4; BvS7,7; PHP13,12; par9; pmg12; sgen100 | decomposition rate: 0.62 ± 0.08; 0.85 ± 0.12; 0.87 ± 0.14; 0.99 ± 0.16; 0.55 ± 0.00; 0.65 ± 0.02; 0.12 ± 0.01; 0.29 ± 0.04 | Helped |
| Use a ρ-backdoor tree found by the proposed search instead of solving the original formula directly | SAT instances with Unit Propagation and CaDiCaL · PvS7,4; BvP7,6; BvP8,4; BvS7,7; PHP13,12; par9; pmg12; sgen100 | decomposition rate: 0.68 ± 0.10; 0.72 ± 0.11; 0.71 ± 0.11; 0.78 ± 0.11; < 0.36 ± 0.04; 0.48 ± 0.04; 0.10 ± 0.01; 0.21 ± 0.03 | Helped |
| Replace probabilistic backdoor-set search with probabilistic backdoor-tree search | SAT decomposition search · SAT instances considered | backdoor construction time: 3 s; 0.5–6 h | Helped |
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