Title
Zero-Suppressed Sentential Decision Diagrams.
Abstract
The Sentential Decision Diagram (SDD) is a prominent knowledge representation language that subsumes the Ordered Binary Decision Diagram (OBDD) as a strict subset. Like OBDDs, SDDs have canonical forms and support bottom-up operations for combining SDDs, but they are more succinct than OBDDs. In this paper we introduce an SDD variant, called the Zero-suppressed Sentential Decision Diagram (ZSDD). The key idea of ZSDD is to employ new trimming rules for obtaining a canonical form. As a result, ZSDD subsumes the Zero-suppressed Binary Decision Diagram (ZDD) as a strict subset. ZDDs are known for their effectiveness on representing sparse Boolean functions. Likewise, ZSDDs can be more succinct than SDDs when representing sparse Boolean functions. We propose several polytime bottom-up operations over ZSDDs, and a technique for reducing ZSDD size, while maintaining applicability to important queries. We also specify two distinct upper bounds on ZSDD sizes; one is derived from the treewidth of a CNF and the other from the size of a family of sets. Experiments show that ZSDDs are smaller than SDDs or ZDDs for a standard benchmark dataset.
Year
Venue
Field
2016
AAAI
Boolean function,Family of sets,Knowledge representation and reasoning,Computer science,Binary decision diagram,Theoretical computer science,Canonical form,Knowledge compilation,Influence diagram,Treewidth
DocType
Citations 
PageRank 
Conference
1
0.36
References 
Authors
4
4
Name
Order
Citations
PageRank
Masaaki Nishino12810.34
Norihito Yasuda27212.56
Shin-ichi Minato372584.72
Masaaki Nagata457377.86