Federica Garin
French Institute for Research in Computer Science and Automation
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Publication
Featured researches published by Federica Garin.
Performance Evaluation | 2018
Stéphane Durand; Federica Garin; Bruno Gaujal
In this paper we design and analyze distributed best response dynamics to compute Nash equilibria in potential games. This algorithm uses local Poisson clocks for each player, and does not rely on the usual but unrealistic assumption that players take no time to compute their best response. If this time (denoted δ) is taken into account, distributed best response dynamics may suffer from overlaps: one player starts to play while another player has not changed its strategy yet. Overlaps may lead to drops of the potential but we can show that they do not jeopardize eventual convergence to a Nash equilibrium. Our main result is to use a Markovian approach to show that the average execution time of the algorithm can be bounded from above by e γ δn log n log log n (1 + o(1)) and from below by δn log n log log n (1 + o(1)), where γ is the Euler constant, n is the number of players and δ is the time taken by one player to compute its best response. These bounds are obtained by using an asymptotically optimal playing rate λ. Our analytic bounds show that this λ is high: ˆ λ = log log n−log log log n δ. This induces a large probability of overlap (ˆ p = 1 − log log n/ log n). In practice, numerical simulations also show that using high playing rates is efficient, with an optimal probability of overlap p opt ≈ 0.78 up to n = 250. This implies that best response dynamics are unexpectedly efficient to compute Nash equilibria, even in a distributed setting.
IEEE Transactions on Control of Network Systems | 2017
Sebin Gracy; Federica Garin; Alain Y. Kibangou
This paper studies linear network systems affected by multiple unknown inputs with the objective of reconstructing both the initial state and the unknown input with one time-step delay. We state conditions under which both the whole network state and the unknown input can be reconstructed from output measurements, over every window of length <inline-formula><tex-math notation=LaTeX>
IEEE Transactions on Control Systems and Technology | 2017
Nicolas Cardoso de Castro; Daniel E. Quevedo; Federica Garin; Carlos Canudas-de-Wit
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european control conference | 2016
Simon Gerwig; Bilal Sari; Federica Garin; Carlos Canudas-de-Wit
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european control conference | 2018
Stéphane Durand; Federica Garin; Bruno Gaujal
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NecSys 2018 - 7th IFAC Workshop on Distributed Estimation and Control in Networked Systems | 2018
Federica Garin; Sebin Gracy; Alain Y. Kibangou
</tex-math></inline-formula> being the dimension of the system, for all system matrices that share a common zero/nonzero pattern (uniform <inline-formula><tex-math notation=LaTeX>
IEEE Transactions on Control Systems and Technology | 2018
Pietro Grandinetti; Carlos Canudas-de-Wit; Federica Garin
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conference on decision and control | 2017
Federica Garin
</tex-math></inline-formula>-step strongly structural input and state observability) or at least for almost all system matrices that share a common zero/nonzero pattern (uniform <inline-formula><tex-math notation=LaTeX>
Archive | 2017
Stéphane Durand; Federica Garin; Bruno Gaujal
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IFAC-PapersOnLine | 2017
Sebin Gracy; Federica Garin; Alain Y. Kibangou
</tex-math></inline-formula>-step structural input and state observability). Based on some specific assumptions on the structure of the interactions between the unknown input and the network states, we show that such a characterization depends only on strongly structural (respectively, structural) observability properties of a suitable subsystem.