Research map / Learning theory and algorithms / Combinatorial and search optimization
Dynamic Controllability of Disjunctive Temporal Networks: Validation and Synthesis of Executable Strategies
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| SMT-based pruning of unfeasible paths (ablation) | Unordered synthesis · DTNU-DC benchmark (3465 instances, 600s limit) | solved instances: 1531 -> 2289 | Helped |
| SMT-based pruning of unfeasible paths (ablation) | Ordered synthesis · DTNU-DC benchmark (3465 instances, 600s limit) | solved instances: 1552 -> 2543 | Helped |
| track ordered instead of unordered sets of scheduled time points (ablation) | SMT-pruned synthesis · DTNU-DC benchmark (3465 instances, 600s limit) | solved instances: 2289 -> 2543 | Helped |
| timed-game synthesis with SMT pruning instead of TIGA encodings | DTNU-DC solving · DTNU-DC benchmark (3465 instances, 600s limit) | solved instances: 799 -> 2543 | Helped |
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