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Conference object . 2023
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https://dx.doi.org/10.48550/ar...
Article . 2023
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Bounds on BDD-Based Bucket Elimination

Authors: Mengel, Stefan;

Bounds on BDD-Based Bucket Elimination

Abstract

We study BDD-based bucket elimination, an approach to satisfiability testing using variable elimination which has seen several practical implementations in the past. We prove that it allows solving the standard pigeonhole principle formulas efficiently, when allowing different orders for variable elimination and BDD-representations, a variant of bucket elimination that was recently introduced. Furthermore, we show that this upper bound is somewhat brittle as for formulas which we get from the pigeonhole principle by restriction, i.e., fixing some of the variables, the same approach with the same variable orders has exponential runtime. We also show that the more common implementation of bucket elimination using the same order for variable elimination and the BDDs has exponential runtime for the pigeonhole principle when using either of the two orders from our upper bound, which suggests that the combination of both is the key to efficiency in the setting.

Keywords

FOS: Computer and information sciences, Computer Science - Artificial Intelligence, Complexity, Binary Decision Diagrams, [INFO] Computer Science [cs], Computational Complexity (cs.CC), 004, Computer Science - Computational Complexity, Artificial Intelligence (cs.AI), Bucket Elimination, Theory of computation → Constraint and logic programming, Theory of computation → Proof complexity, Satisfiability, ddc: ddc:004

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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