Local Stackelberg Equilibrium Seeking in Generalized Aggregative Games

• 成果类型: Article
• 署名作者: Fabiani, Filippo; Tajeddini, Mohammad Amin; Kebriaei, Hamed; Grammatico, Sergio
• 署名单位: University of Oxford; University of Tehran; Delft University of Technology
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2021.3077874
• 发表日期: 2022
• 页码: 965-970
• 关键词: games; cost function; Couplings; STANDARDS; Approximation algorithms; CONVERGENCE; wireless networks; game theory; hierarchical systems; optimization; Stackelberg equilibrium

摘要

We propose a two-layer, semidecentralized algorithm to compute a local solution to the Stackelberg equilibrium problem in aggregative games with coupling constraints. Specifically, we focus on a single-leader, multiple-follower problem, and after equivalently recasting the Stackelberg game as a mathematical program with complementarity constraints (MPCC), we iteratively convexify a regularized version of the MPCC as the inner problem, whose solution generates a sequence of feasible descent directions for the original MPCC. Thus, by pursuing a descent direction at every outer iteration, we establish convergence to a local Stackelberg equilibrium. Finally, the proposed algorithm is tested on a numerical case study, a hierarchical instance of the charging coordination problem of plug-in electric vehicles.