Research map / Learning theory and algorithms / Combinatorial and search optimization
totSAT - Totally-Ordered Hierarchical Planning Through SAT
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use SAT-based totSAT instead of HTN2STRIPS | HTN planning · 127 totally-ordered instances | instances solved: 82 -> 125 | Helped |
| use totSAT instead of SHOP | HTN planning · 127 instances | instances solved: 92 -> 125 | Helped |
| swap SAT solver (cryptominisat5, MapleCOMSPS, Riss6, minisat) (ablation) | totSAT · 127 instances | instances solved: 123 to 125 | No clear effect |
| use plain minisat instead of cryptominisat5 (ablation) | totSAT · TRANSPORT | instances solved: 28 -> 27 | Hurt |
| use plan-space heuristics (TDG) instead of blind BFS | PANDA planners · 127 instances | instances solved: 62 (BFS) vs 62 (TDG-c), 68 (TDG-m) | Mixed |
| use totSAT instead of SHOP for solution length | HTN planning · solution quality | extra actions vs optimal: +0.37 -> 0.58 | Hurt |
Closest papers by meaning
- Bringing Order to Chaos – A Compact Representation of Partial Order in SAT-Based HTN Planning (AAAI 2019 · similarity 0.93)
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