Learning Ordered Binary Decision Diagrams

@inproceedings{Gavald1995LearningOB,
  title={Learning Ordered Binary Decision Diagrams},
  author={Ricard Gavald{\`a} and David Guijarro},
  booktitle={ALT},
  year={1995}
}
This note studies the learnability of ordered binary decision diagrams (obdds). We give a polynomial-time algorithm using membership and equivalence queries that finds the minimum obdd for the target respecting a given ordering. We also prove that both types of queries and the restriction to a given ordering are necessary if we want minimality in the output, unless P=NP. If learning has to occur with respect to the optimal variable ordering, polynomial-time learnability implies the… 

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TLDR
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TLDR
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TLDR
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TLDR
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Lower Bounds for Testing Computability by Small Width OBDDs

TLDR
This work considers the problem of testing whether a function f is computable by a read-once, width-2 ordered binary decision diagram (OBDD), and shows that for any constant w ≥ 4, Ω(n) queries are required, resolving a conjecture of Goldreich.

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