A Distributed Algorithm For Almost-Nash Equilibria of Average Aggregative Games With Coupling Constraints

Open access
Date
2020-06Type
- Journal Article
Citations
Cited 16 times in
Web of Science
Cited 19 times in
Scopus
ETH Bibliography
yes
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Abstract
We consider the framework of average aggregative games, where the cost function of each agent depends on his own strategy and on the average population strategy. We focus on the case in which the agents are coupled not only via their cost functions, but also via a shared constraint coupling their strategies. We propose a distributed algorithm that achieves an ε -Nash equilibrium by requiring only local communications of the agents, as specified by a sparse communication network. The proof of convergence of the algorithm relies on the auxiliary class of network aggregative games. We apply our theoretical findings to a multimarket Cournot game with transportation costs and maximum market capacity. © 2019 IEEE. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000424125Publication status
publishedExternal links
Journal / series
IEEE Transactions on Control of Network SystemsVolume
Pages / Article No.
Publisher
IEEESubject
Aggregative games; Coupling constraints; Generalized Nash equilibrium; Distributed algorithms; Largescale systems; Cournot gameOrganisational unit
03751 - Lygeros, John / Lygeros, John
Funding
787845 - Optimal control at large (EC)
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Show all metadata
Citations
Cited 16 times in
Web of Science
Cited 19 times in
Scopus
ETH Bibliography
yes
Altmetrics