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Enumerating Independent Linear Inferences

LMCS vol.Volume 19, Issue 22023
Anupam Das, Alex Rice

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原文摘要(Abstract)

A linear inference is a valid inequality of Boolean algebra in which each variable occurs at most once on each side. In this work we leverage recently developed graphical representations of linear formulae to build an implementation that is capable of more efficiently searching for switch-medial-independent inferences. We use it to find four `minimal' 8-variable independent inferences and also prove that no smaller ones exist; in contrast, a previous approach based directly on formulae reached computational limits already at 7 variables. Two of these new inferences derive some previously found independent linear inferences. The other two (which are dual) exhibit structure seemingly beyond the scope of previous approaches we are aware of; in particular, their existence contradicts a conjecture of Das and Strassburger. We were also able to identify 10 minimal 9-variable linear inferences independent of all the aforementioned inferences, comprising 5 dual pairs, and present applications of our implementation to recent `graph logics'.

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DOI 原文 ·

BibTeX
@article{paperbot2216,
  title = {Enumerating Independent Linear Inferences},
  author = {Anupam Das and Alex Rice},
  journal = {Logical Methods in Computer Science},
  volume = {Volume 19, Issue 2},
  year = {2023},
  doi = {10.46298/lmcs-19(2:11)2023}
}