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On the Computation of Paracoherent Answer Sets

AAAI 2017 · Learning theory and algorithms › Combinatorial and search optimization · approach: Logic and answer set programming theory · 15 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Replace full answer-set enumeration with Guess&CheckWASP paracoherent-answer-set computation · Semi-stable ASP competition instancesinstances solved: 0 -> 68Helped
Replace full answer-set enumeration with MinimizeWASP paracoherent-answer-set computation · Semi-stable ASP competition instancesinstances solved: 0 -> 78Helped
Replace full answer-set enumeration with SplitWASP paracoherent-answer-set computation · Semi-stable ASP competition instancesinstances solved: 0 -> 78Helped
Use weak-constraint optimization instead of enumerationWASP paracoherent-answer-set computation · Semi-stable ASP competition instancesinstances solved: 0 -> 15Helped
Use Minimize or Split instead of Guess&CheckWASP paracoherent-answer-set computation · Semi-stable ASP competition instancesinstances solved: 68 -> 78Helped
Use Split instead of MinimizeWASP semi-equilibrium computation · ASP competition instancesinstances solved: 13 -> 18Helped
Apply semi-equilibrium rather than semi-stable semanticsWASP paracoherent-answer-set algorithms · ASP competition instancesinstances solvedHurt
Use Minimize rather than FilteringWASP paracoherent-answer-set computation · Semi-equilibrium ASP competition instancesinstances solved: 0 -> 13Helped
Use Split rather than FilteringWASP paracoherent-answer-set computation · Semi-equilibrium ASP competition instancesinstances solved: 0 -> 18Helped
Use Minimize rather than SplitWASP paracoherent-answer-set computation · Semi-stable ASP competition instancesinstances solved: 78 -> 78No clear effect

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