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A Coevolutionary Model of Strategic Network Formation

  • Conference paper
Complex Networks V

Part of the book series: Studies in Computational Intelligence ((SCI,volume 549))

Abstract

In foundational models of network formation, the mechanisms for link formation are based solely on network topology. For example, preferential attachment uses degree distributions, whereas a strategic connections model uses internode distances. These dynamics implicitly presume that such benefits and costs are instantaneous functions of the network topology. A more detailed model would include that benefits and costs are themselves derived through a dynamic process, which, in the absence of time-scale separation, necessitates a coevolutionary analysis. This paper introduces a new coevolutionary model of strategic network formation. In this model, network formation evolves along with the flow of benefits from one node to another. We examine the emergent equilibria of this combined dynamics of network formation and benefit flow.We show that the class of strict equilibria is stable (or robust to small perturbations in the benefits flows).

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Authors and Affiliations

  1. School of Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta, GA, 30308, USA

    Ibrahim Al-Shyoukh & Jeff S. Shamma

Authors
  1. Ibrahim Al-Shyoukh
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  2. Jeff S. Shamma
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Editor information

Editors and Affiliations

  1. Department of Mathematics, University of Bologna, Bologna, Italy

    Pierluigi Contucci

  2. Florida Institute of Technology Dept. Computer Sciences, Melbourne, FL, Florida, USA

    Ronaldo Menezes

  3. Department of Computer Science, University of Bologna, Bologna, Italy

    Andrea Omicini

  4. Room E-136, Northwestern University, Evanston, Illinois, USA

    Julia Poncela-Casasnovas

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© 2014 Springer International Publishing Switzerland

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Al-Shyoukh, I., Shamma, J.S. (2014). A Coevolutionary Model of Strategic Network Formation. In: Contucci, P., Menezes, R., Omicini, A., Poncela-Casasnovas, J. (eds) Complex Networks V. Studies in Computational Intelligence, vol 549. Springer, Cham. https://doi.org/10.1007/978-3-319-05401-8_16

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  • DOI: https://doi.org/10.1007/978-3-319-05401-8_16

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-05400-1

  • Online ISBN: 978-3-319-05401-8

  • eBook Packages: EngineeringEngineering (R0)

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