Advanced

Controlling Evolutionary Dynamics in Networks : A Case Study

Zino, Lorenzo; Como, Giacomo LU and Fagnani, Fabio (2018) In IFAC-PapersOnLine 51(23). p.349-354
Abstract

Due to their wide adaptability to different application fields spanning from opinion dynamics to biology, the analysis of evolutionary dynamics is a compelling problem in the science of networks and systems. In this paper, we deal with controlled evolutionary dynamics in networks. We discuss a novel approach to model these phenomena, which enables us to estimate the duration of the process depending on the network topology and on the control policy adopted. In a previous work, we have presented some preliminary results including a feedback control policy to speed up the dynamics. These encouraging results have pushed us toward deeper analysis of the problem. Here, we exhibit some critical issues concerning the feedback control policy... (More)

Due to their wide adaptability to different application fields spanning from opinion dynamics to biology, the analysis of evolutionary dynamics is a compelling problem in the science of networks and systems. In this paper, we deal with controlled evolutionary dynamics in networks. We discuss a novel approach to model these phenomena, which enables us to estimate the duration of the process depending on the network topology and on the control policy adopted. In a previous work, we have presented some preliminary results including a feedback control policy to speed up the dynamics. These encouraging results have pushed us toward deeper analysis of the problem. Here, we exhibit some critical issues concerning the feedback control policy originally proposed, which limit its applicability to real-world scenarios, and we address them by proposing a new improved control policy. Finally, using Monte Carlo simulations, we test the effectiveness of our approach to evolutionary dynamics and of the new control policy proposed here, against a real-world scenario, obtaining an extremely promising outcome for our future research.

(Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Control over Networks, Evolutionary Dynamics, Feedback Control, Graph-based methods for networked control, Multi-Agent Systems
in
IFAC-PapersOnLine
volume
51
issue
23
pages
6 pages
publisher
IFAC Secretariat
external identifiers
  • scopus:85058472972
ISSN
2405-8963
DOI
10.1016/j.ifacol.2018.12.060
language
English
LU publication?
yes
id
90f24bee-08fc-4134-ab99-ec20812d54df
date added to LUP
2019-01-10 09:40:52
date last changed
2019-01-10 09:40:52
@article{90f24bee-08fc-4134-ab99-ec20812d54df,
  abstract     = {<p>Due to their wide adaptability to different application fields spanning from opinion dynamics to biology, the analysis of evolutionary dynamics is a compelling problem in the science of networks and systems. In this paper, we deal with controlled evolutionary dynamics in networks. We discuss a novel approach to model these phenomena, which enables us to estimate the duration of the process depending on the network topology and on the control policy adopted. In a previous work, we have presented some preliminary results including a feedback control policy to speed up the dynamics. These encouraging results have pushed us toward deeper analysis of the problem. Here, we exhibit some critical issues concerning the feedback control policy originally proposed, which limit its applicability to real-world scenarios, and we address them by proposing a new improved control policy. Finally, using Monte Carlo simulations, we test the effectiveness of our approach to evolutionary dynamics and of the new control policy proposed here, against a real-world scenario, obtaining an extremely promising outcome for our future research.</p>},
  author       = {Zino, Lorenzo and Como, Giacomo and Fagnani, Fabio},
  issn         = {2405-8963},
  keyword      = {Control over Networks,Evolutionary Dynamics,Feedback Control,Graph-based methods for networked control,Multi-Agent Systems},
  language     = {eng},
  number       = {23},
  pages        = {349--354},
  publisher    = {IFAC Secretariat},
  series       = {IFAC-PapersOnLine},
  title        = {Controlling Evolutionary Dynamics in Networks : A Case Study},
  url          = {http://dx.doi.org/10.1016/j.ifacol.2018.12.060},
  volume       = {51},
  year         = {2018},
}