Distributed seeking of nash equilibria with applications to mobile sensor networks

Miloš S. Stanković, Karl H. Johansson, Dušan M. Stipanović

Research output: Contribution to journalArticlepeer-review


We consider the problem of distributed convergence to a Nash equilibrium in a noncooperative game where the players generate their actions based only on online measurements of their individual cost functions, corrupted with additive measurement noise. Exact analytical forms and/or parameters of the cost functions, as well as the current actions of the players may be unknown. Additionally, the players' actions are subject to linear dynamic constraints. We propose an algorithm based on discrete-time stochastic extremum seeking using sinusoidal perturbations and prove its almost sure convergence to a Nash equilibrium. We show how the proposed algorithm can be applied to solving coordination problems in mobile sensor networks, where motion dynamics of the players can be modeled as: 1) single integrators (velocity-actuated vehicles), 2) double integrators (force-actuated vehicles), and 3) unicycles (a kinematic model with nonholonomic constraints). Examples are given in which the cost functions are selected such that the problems of connectivity control, formation control, rendezvous and coverage control are solved in an adaptive and distributed way. The methodology is illustrated through simulations.

Original languageEnglish (US)
Article number6069543
Pages (from-to)904-919
Number of pages16
JournalIEEE Transactions on Automatic Control
Issue number4
StatePublished - Apr 2012


  • Convergence
  • Nash equilibrium
  • extremum seeking
  • learning
  • mobile sensor networks
  • multi-agent control
  • noncooperative games
  • stochastic optimization

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


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