Research map / Learning theory and algorithms / Combinatorial and search optimization
Rushing and Strolling among Answer Sets – Navigation Made Easy
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use facet-counting weights rather than absolute weights for strictly goal-oriented navigation | fasb on PC configuration · PC configuration | runtime | Helped |
| Use facet-counting weights rather than absolute weights for strictly goal-oriented navigation | fasb on stable argumentation · Stable argumentation | steps to unique solution: 6 vs 5 | Hurt |
| Use facet-counting weights rather than absolute weights for explore navigation | fasb on stable argumentation · Stable argumentation | execution time per step | Mixed |
| Apply weighted navigation to preferred rather than stable argumentation | fasb · Preferred argumentation | feasibility across navigation modes | Hurt |
| Use facet-counting weights to prioritize a navigation facet | strictly goal-oriented navigation · PC configuration | execution time: 35% | Helped |
| Use absolute weights to select the highest-pace facet | strictly goal-oriented navigation · Stable argumentation | solutions pruned: 93%; 7152 out of 7696 | Helped |
| Use relative facet-counting weights instead of absolute solution counts | weighted faceted navigation · ASP answer-set spaces | computational feasibility | Helped |
| Use supported-model counting instead of answer-set counting on tight programs | weighted faceted navigation · Tight ASP programs | weight agreement with absolute weights | No clear effect |
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