Compiling Constraint Networks into Multivalued Decomposable Decision Graphs
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Main Track. Pages 332-337.
Abstract
We present and evaluate a top-down algorithm for compiling finite-domain constraint networks (CNs) into the language MDDG of multivalued decomposable decision graphs. Though it includes Decision-DNNF as a proper subset, MDDG offers the same key tractable queries and transformations as Decision-DNNF, which makes it useful for many applications. Intensive experiments showed that our compiler cn2mddg succeeds in compiling CNs which are out of the reach of standard approaches based on a translation of the input network to CNF, followed by a compilation to Decision-DNNF. Furthermore, the sizes of the resulting compiled representations turn out to be much smaller (sometimes by several orders of magnitude).
@inproceedings{ijcai2015p53,
title = {Compiling Constraint Networks into Multivalued Decomposable Decision Graphs},
author = {Koriche, Frédéric and Lagniez, Jean-Marie and Marquis, Pierre and Thomas, Samuel},
booktitle = {Proceedings of the Twenty-Fourth International Joint Conference on
Artificial Intelligence, {IJCAI-15}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Qiang Yang and Michael Wooldridge},
pages = {332--337},
year = {2015},
month = {7},
note = {Main Track},
url = {https://ijcai.org/proceedings/2015/53},
}
TY - CPAPER TI - Compiling Constraint Networks into Multivalued Decomposable Decision Graphs AU - Koriche, Frédéric AU - Lagniez, Jean-Marie AU - Marquis, Pierre AU - Thomas, Samuel T2 - Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15 PB - International Joint Conferences on Artificial Intelligence PY - 2015 SP - 332 EP - 337 UR - https://ijcai.org/proceedings/2015/53 ER -Copied
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