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https://dx.doi.org/10.48550/ar...
Article . 2009
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
DBLP
Conference object . 2018
Data sources: DBLP
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Strong, Weak and Branching Bisimulation for Transition Systems and Markov Reward Chains: A Unifying Matrix Approach

Authors: Trcka, N.;

Strong, Weak and Branching Bisimulation for Transition Systems and Markov Reward Chains: A Unifying Matrix Approach

Abstract

We first study labeled transition systems with explicit successful termination. We establish the notions of strong, weak, and branching bisimulation in terms of boolean matrix theory, introducing thus a novel and powerful algebraic apparatus. Next we consider Markov reward chains which are standardly presented in real matrix theory. By interpreting the obtained matrix conditions for bisimulations in this setting, we automatically obtain the definitions of strong, weak, and branching bisimulation for Markov reward chains. The obtained strong and weak bisimulations are shown to coincide with some existing notions, while the obtained branching bisimulation is new, but its usefulness is questionable.

Country
Netherlands
Keywords

D.2.1, FOS: Computer and information sciences, Computer Science - Logic in Computer Science, D.3.1, Computer Science - Performance, D.2.4, QA75.5-76.95, Logic in Computer Science (cs.LO), Performance (cs.PF), Electronic computers. Computer science, D.3.1; D.2.1; D.2.4; F.3.1, QA1-939, F.3.1, Mathematics

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Average
Green
gold