Compressing Binary Decision Diagrams
Artificial Intelligence
2008-12-18 v1 Distributed, Parallel, and Cluster Computing
Abstract
The paper introduces a new technique for compressing Binary Decision Diagrams in those cases where random access is not required. Using this technique, compression and decompression can be done in linear time in the size of the BDD and compression will in many cases reduce the size of the BDD to 1-2 bits per node. Empirical results for our compression technique are presented, including comparisons with previously introduced techniques, showing that the new technique dominate on all tested instances.
Cite
@article{arxiv.0805.3267,
title = {Compressing Binary Decision Diagrams},
author = {Esben Rune Hansen and S. Srinivasa Rao and Peter Tiedemann},
journal= {arXiv preprint arXiv:0805.3267},
year = {2008}
}
Comments
Full (tech-report) version of ECAI 2008 short paper