Distributed equilibrium seeking in aggregative games: linear convergence under singular perturbations lens

We present a fully-distributed algorithm for Nash equilibrium seeking in aggregative games over networks. The proposed scheme endows each agent with a gradient-based scheme equipped with a tracking mechanism to locally reconstruct the aggregative variable, which is not available to the agents. We sh...

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Main Authors: Carnevale, G, Fabiani, F, Fele, F, Margellos, K, Notarstefano, G
Format: Conference item
Language:English
Published: 2024
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author Carnevale, G
Fabiani, F
Fele, F
Margellos, K
Notarstefano, G
author_facet Carnevale, G
Fabiani, F
Fele, F
Margellos, K
Notarstefano, G
author_sort Carnevale, G
collection OXFORD
description We present a fully-distributed algorithm for Nash equilibrium seeking in aggregative games over networks. The proposed scheme endows each agent with a gradient-based scheme equipped with a tracking mechanism to locally reconstruct the aggregative variable, which is not available to the agents. We show that our method falls into the framework of singularly perturbed systems, as it involves the interconnection between a fast subsystem – the global information reconstruction dynamics – with a slow one concerning the optimization of the local strategies. This perspective plays a key role in analyzing the scheme with a constant stepsize, and in proving its linear convergence to the Nash equilibrium in strongly monotone games with local constraints. By exploiting the flexibility of our aggregative variable definition (not necessarily the arithmetic average of the agents’ strategy), we show the efficacy of our algorithm on a realistic voltage support case study for the smart grid.
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spelling oxford-uuid:c08b9f32-2f37-45ea-b95b-8dd441805d312024-07-26T10:07:56ZDistributed equilibrium seeking in aggregative games: linear convergence under singular perturbations lensConference itemhttp://purl.org/coar/resource_type/c_5794uuid:c08b9f32-2f37-45ea-b95b-8dd441805d31EnglishSymplectic Elements2024Carnevale, GFabiani, FFele, FMargellos, KNotarstefano, GWe present a fully-distributed algorithm for Nash equilibrium seeking in aggregative games over networks. The proposed scheme endows each agent with a gradient-based scheme equipped with a tracking mechanism to locally reconstruct the aggregative variable, which is not available to the agents. We show that our method falls into the framework of singularly perturbed systems, as it involves the interconnection between a fast subsystem – the global information reconstruction dynamics – with a slow one concerning the optimization of the local strategies. This perspective plays a key role in analyzing the scheme with a constant stepsize, and in proving its linear convergence to the Nash equilibrium in strongly monotone games with local constraints. By exploiting the flexibility of our aggregative variable definition (not necessarily the arithmetic average of the agents’ strategy), we show the efficacy of our algorithm on a realistic voltage support case study for the smart grid.
spellingShingle Carnevale, G
Fabiani, F
Fele, F
Margellos, K
Notarstefano, G
Distributed equilibrium seeking in aggregative games: linear convergence under singular perturbations lens
title Distributed equilibrium seeking in aggregative games: linear convergence under singular perturbations lens
title_full Distributed equilibrium seeking in aggregative games: linear convergence under singular perturbations lens
title_fullStr Distributed equilibrium seeking in aggregative games: linear convergence under singular perturbations lens
title_full_unstemmed Distributed equilibrium seeking in aggregative games: linear convergence under singular perturbations lens
title_short Distributed equilibrium seeking in aggregative games: linear convergence under singular perturbations lens
title_sort distributed equilibrium seeking in aggregative games linear convergence under singular perturbations lens
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AT fabianif distributedequilibriumseekinginaggregativegameslinearconvergenceundersingularperturbationslens
AT felef distributedequilibriumseekinginaggregativegameslinearconvergenceundersingularperturbationslens
AT margellosk distributedequilibriumseekinginaggregativegameslinearconvergenceundersingularperturbationslens
AT notarstefanog distributedequilibriumseekinginaggregativegameslinearconvergenceundersingularperturbationslens