Abstract
In this paper, we propose a new algorithm which exactly learns ordered binary decision diagrams (OBDDs) with a given variable ordering via equivalence queries and membership queries. Our algorithm uses at most n equivalence queries and at most 2n([log2 m] + 3n) membership queries, where n is the number of nodes in the target reduced OBDD and m is the number of variables. We have reduced the number of membership queries by a factor of m compared with the best known algorithm for this problem due to Gavaldà and Guijarro.
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© 1997 Springer-Verlag Berlin Heidelberg
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Nakamura, A. (1997). An efficient exact learning algorithm for ordered binary decision diagrams. In: Li, M., Maruoka, A. (eds) Algorithmic Learning Theory. ALT 1997. Lecture Notes in Computer Science, vol 1316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63577-7_51
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DOI: https://doi.org/10.1007/3-540-63577-7_51
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