Microtheory: Approximate Nash equilibria in large nonconvex aggregative games
Published: 14 January 2022
1 February. Dr Cheng Wan, EDF Lab, Paris-Saclay
Dr Cheng Wan, EDF Lab, Paris-Saclay
'Approximate Nash Equilibria in Large Nonconvex Aggregative Games' (co-authored by K. Liu and N. Oudjane)
Tuesday 1 February, 1.00pm-2.30pm
Zoom online seminar
Abstract
This paper shows the existence of O(1/n^γ)-Nash equilibria in n-player noncooperative sum-aggregative games where the players' cost functions depend only on their own action and the average of all players' actions, and are lower semicontinuous in the former while γ-Hölder continuous in the latter. Neither the action sets nor the cost functions need to be convex. For an important class of sum-aggregative games which includes congestion games with γ being 1, a gradient-proximal algorithm is used to construct an O(1/n)-Nash equilibria with at most O(n^3) iterations. These results are applied to a numerical example of demand-side management of the electricity system. The asymptotic performance of the algorithm is illustrated when n tends to infinity.
Biography
Cheng Wan earned a BSc degree in Mathematics from Fudan University (China), an engineer diploma at Ecole Polytechnique (France) and a MSc followed by a PhD degree in Mathematics (specialised in Game Theory) at Pierre and Marie Curie University (now Sorbonne University). From 2013 to 2018, she worked successively as a Research Fellow in Economics at University of Oxford and an Assistant Professor in Public Economics at Shanghai University of Finance and Economics. Since 2019, she has been working as a Research Engineer at EDF (Electricity of France).
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First published: 14 January 2022
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