Ensure Differential Privacy and Convergence Accuracy in Consensus Tracking and Aggregative Games with Coupling Constraints. (arXiv:2210.16395v1 [cs.GT])

We address differential privacy for fully distributed aggregative games with
shared coupling constraints. By co-designing the generalized Nash equilibrium
(GNE) seeking mechanism and the differential-privacy noise injection mechanism,
we propose the first GNE seeking algorithm that can ensure both provable
convergence to the GNE and rigorous epsilon-differential privacy, even with the
number of iterations tending to infinity. As a basis of the co-design, we also
propose a differentially private consensus-tracking algorithm that can achieve
rigorous epsilon-differential privacy while maintaining accurate …

constraints convergence differential privacy games privacy tracking