The impact of Entropy and Solution Density on selected SAT heuristics
June 18, 2017 Β· Declared Dead Β· π Entropy
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Authors
Dor Cohen, Ofer Strichman
arXiv ID
1706.05637
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.LO
Citations
0
Venue
Entropy
Last Checked
4 months ago
Abstract
In a recent article [Oh'15], Oh examined the impact of various key heuristics (e.g., deletion strategy, restart policy, decay factor, database reduction) in competitive SAT solvers. His key findings are that their expected success depends on whether the input formula is satisfiable or not. To further investigate these findings, we focused on two properties of satisfiable formulas: the entropy of the formula, which approximates the freedom we have in assigning the variables, and the solution density, which is the number of solutions divided by the search space. We found that both predict better the effect of these heuristics, and that satisfiable formulas with small entropy `behave' similarly to unsatisfiable formulas.
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