Generalized Nash equilibrium seeking for directed nonsmooth multi-cluster games via a distributed Lipschitz algorithm

Yue Wei, Xianlin Zeng, Hao Fang, Yulong Ding, Shuxin Ding

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

This paper investigates a generalized Nash equilibrium (GNE) seeking strategy for a class of nonsmooth multi-cluster games. Each cluster consists of several players. The inter-cluster graph is directed and weight-unbalanced. Moreover, in contrast to previous works of multi-cluster games, coupled nonsmooth inequality constraints, resource allocation constraints, and nonsmooth payoff functions are considered simultaneously in these multi-cluster games. For seeking the GNE of these games, a distributed Lipschitz algorithm with the proximal-splitting scheme is proposed. Then convergence analysis of this designed algorithm is deduced based on Lyapunov stability theory and convex optimization theory. Finally, some simulation results are provided in this paper, which show the efficacy of the distributed GNE seeking algorithm.

Original languageEnglish
Pages (from-to)1-10
Number of pages10
JournalIEEE Transactions on Control of Network Systems
DOIs
Publication statusAccepted/In press - 2024

Keywords

  • Clustering algorithms
  • Convergence
  • Directed graphs
  • Distributed GNE seeking
  • Distributed algorithms
  • Games
  • Heuristic algorithms
  • Linear matrix inequalities
  • Multi-cluster games
  • Nonsmooth functions
  • Proximal operator
  • Resource management

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