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VOSS
2004
Springer

Symbolic Representations and Analysis of Large Probabilistic Systems

9 years 3 months ago
Symbolic Representations and Analysis of Large Probabilistic Systems
Abstract. This paper describes symbolic techniques for the construction, representation and analysis of large, probabilistic systems. Symbolic approaches derive their efficiency by exploiting high-level structure and regularity in the models to which they are applied, increasing the size of the state spaces which can be tackled. In general, this is done by using data structures which provide compact storage but which are still efficient to manipulate, usually based on binary decision diagrams (BDDs) or their extensions. In this paper we focus on BDDs, multi-valued decision diagrams (MDDs), multi-terminal binary decision diagrams (MTBDDs) and matrix diagrams.
Andrew S. Miner, David Parker
Added 02 Jul 2010
Updated 02 Jul 2010
Type Conference
Year 2004
Where VOSS
Authors Andrew S. Miner, David Parker
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