The mean drift: tailoring the mean field theory of markov processes for real-world applications

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Samenvatting

The statement of the mean field approximation theorem in the mean field theory of Markov processes particularly targets the behaviour of population processes with an unbounded number of agents. However, in most real-world engineering applications one faces the problem of analysing middle-sized systems in which the number of agents is bounded. In this paper we build on previous work in this area and introduce the mean drift. We present the concept of population processes and the conditions under which the approximation theorems apply, and then show how the mean drift can be linked to observations which follow from the propagation of chaos. We then use the mean drift to construct a new set of ordinary differential equations which address the analysis of population processes with an arbitrary size.

Originele taal-2Engels
TitelAnalytical and Stochastic Modelling Techniques and Applications
Subtitel24th International Conference, ASMTA 2017, Newcastle-upon-Tyne, UK, July 10-11, 2017, Proceedings
RedacteurenN. Thomas, M. Forshaw
Plaats van productieDordrecht
UitgeverijSpringer
Pagina's196-211
Aantal pagina's16
ISBN van elektronische versie978-3-319-61428-1
ISBN van geprinte versie978-3-319-61427-4
DOI's
StatusGepubliceerd - 2017
Evenement24th International Conference on Analytical and Stochastic Modelling Techniques and Applications, (ASMTA 2017), 10-12 July 2017, Newcastle-upon-Tyne, UK - Newcastle-upon-Tyne, Verenigd Koninkrijk
Duur: 10 jul. 201712 jul. 2017
http://asmta.ugent.be/

Publicatie series

NaamLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10378 LNCS
ISSN van geprinte versie0302-9743
ISSN van elektronische versie1611-3349

Congres

Congres24th International Conference on Analytical and Stochastic Modelling Techniques and Applications, (ASMTA 2017), 10-12 July 2017, Newcastle-upon-Tyne, UK
Verkorte titelASMTA 2017
Land/RegioVerenigd Koninkrijk
StadNewcastle-upon-Tyne
Periode10/07/1712/07/17
Internet adres

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