Ward, JA orcid.org/0000-0002-2469-7768 and Evans, J
(2019)
A General Model of Dynamics on Networks with Graph Automorphism Lumping.
In: Aiello, LM, Cherifi, C, Cherifi, H, Lambiotte, R, Lió, P and Rocha, LM, (eds.)
Studies in Computational Intelligence.
7th International Conference on Complex Networks and Their Applications (Complex Networks 2018), 11-13 Dec 2018, Cambridge, UK.
Springer
, pp. 445-456.
ISBN 9783030054106
Abstract
In this paper we introduce a general Markov chain model of dynamical processes on networks. In this model, nodes in the network can adopt a finite number of states and transitions can occur that involve multiple nodes changing state at once. The rules that govern transitions only depend on measures related to the state and structure of the network and not on the particular nodes involved. We prove that symmetries of the network can be used to lump equivalent states in state-space. We illustrate how several examples of well-known dynamical processes on networks correspond to particular cases of our general model. This work connects a wide range of models specified in terms of node-based dynamical rules to their exact continuous-time Markov chain formulation.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © Springer Nature Switzerland AG 2019 . This is an author produced version of a paper published in Complex Networks and Their Applications VII and their Applications (SCI, volume 812). Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Dynamics on networks; Markov chains; Graph automorphisms; Lumping; Epidemic models; Opinion dynamics; Social physics |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Applied Mathematics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 09 Jan 2019 15:36 |
Last Modified: | 02 Dec 2019 01:41 |
Status: | Published |
Publisher: | Springer |
Identification Number: | 10.1007/978-3-030-05411-3_36 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:140774 |