ON THE STABILITY OF AN ADAPTIVE LEARNING DYNAMICS IN TRAFFIC GAMES

Miguel A. Dumett, Roberto Cominetti

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This paper investigates the dynamic stability of an adaptive learning procedure in a traffic game. Using the Routh-Hurwitz criterion we study the stability of the rest points of the corresponding mean field dynamics. In the special case with two routes and two players we provide a full description of the number and nature of these rest points as well as the global asymptotic behavior of the dynamics. Depending on the parameters of the model, we find that there are either one, two or three equilibria and we show that in all cases the mean field trajectories converge towards a rest point for almost all initial conditions.

Original languageEnglish
Pages (from-to)265-282
Number of pages18
JournalJournal of Dynamics and Games
Volume5
Issue number4
DOIs
StatePublished - 2018
Externally publishedYes

Keywords

  • Congestion games
  • Routh-Hurwitz criterion
  • adaptive learning dynamics
  • dynamical systems
  • routing equilibrium
  • stability
  • stochastic algorithms

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