  Continuous-time gradient-based Nash equilibrium seeking algorithms enjoy a
passivity property under a suitable monotonicity assumption. This feature has
been exploited to design distributed algorithms that converge to Nash
equilibria and use local information only. We further exploit the passivity
property to interconnect the algorithms with distributed averaging integral
controllers that tune on-line the weights of the communication graph. The main
advantage is to guarantee convergence to a Nash equilibrium without requiring a
strong coupling condition on the algebraic connectivity of the communication
graph over which the players exchange information, nor a global high-gain.
