Name
Abstract | ||
|---|---|---|
In this paper we present an overview of the field of deterministic approximation of Markov processes, both in discrete and continuous times. We will discuss mean field approximation of discrete time Markov chains and fluid approximation of continuous time Markov chains, considering the cases in which the deterministic limit process lives in continuous time or discrete time. We also consider some more advanced results, especially those relating to the limit stationary behaviour. We assume a knowledge of modelling with Markov chains, but not of more advanced topics in stochastic processes. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.peva.2013.01.001 | Perform. Eval. |
Keywords | Field | DocType |
discrete time markov chain,mean field approximation,continuous approximation,collective system behaviour,fluid approximation,discrete time,markov chain,deterministic approximation,advanced result,continuous time markov chain,continuous time,advanced topic,markov chains | Statistical physics,Mathematical optimization,Markov process,Markov property,Computer science,Markov chain,Balance equation,Discrete phase-type distribution,Time reversibility,Examples of Markov chains,Distributed computing,Markov renewal process | Journal |
Volume | Issue | ISSN |
70 | 5 | 0166-5316 |
Citations | PageRank | References |
44 | 1.44 | 41 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Luca Bortolussi | 1 | 663 | 58.88 |
| Jane Hillston | 2 | 1657 | 125.09 |
| Diego Latella | 3 | 1168 | 113.42 |
| Mieke Massink | 4 | 1095 | 87.58 |