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Learning ordered binary decision diagrams

  • Ricard Gavaldà
  • David Guijarro
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 997)

Abstract

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 approximability of two NP-hard optimization problems: the problem of finding the optimal variable ordering for a given obdd and the Optimal Linear Arrangement problem on graphs.

Keywords

Polynomial Time Boolean Function Binary Decision Diagram Membership Query Deterministic Finite Automaton 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Ricard Gavaldà
    • 1
  • David Guijarro
    • 1
  1. 1.Department of Software (LSI)Universitat Politècnica de CatalunyaBarcelonaSpain

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