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Farzad Salehisadaghiani

Bio: Farzad Salehisadaghiani is an academic researcher from University of Toronto. The author has contributed to research in topics: Nash equilibrium & Best response. The author has an hindex of 7, co-authored 18 publications receiving 319 citations. Previous affiliations of Farzad Salehisadaghiani include Concordia University & Concordia University Wisconsin.

Papers
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Journal ArticleDOI
TL;DR: An asynchronous gossip-based algorithm for finding a Nash equilibrium of a game in a distributed multi-player network designed in such a way that players make decisions based on estimates of the other players' actions obtained from local neighbors is presented.

241 citations

Journal ArticleDOI
TL;DR: A relatively fast algorithm is developed within the framework of inexact-ADMM, based on local information exchange between the players, that convergence to Nash equilibrium for fixed step-sizes is proved and its convergence rate is analysed.

77 citations

Proceedings ArticleDOI
01 Dec 2014
TL;DR: An asynchronous gossip-based algorithm is proposed for finding a Nash equilibrium of a game in a distributed multi-player network that is designed in such a way that the players' actions are updated based on the estimates of the other players'actions which are obtained from the local neighbors.
Abstract: In this paper an asynchronous gossip-based algorithm is proposed for finding a Nash equilibrium of a game in a distributed multi-player network. The algorithm is designed in such a way that the players' actions are updated based on the estimates of the other players' actions which are obtained from the local neighbors. The almost sure convergence proof of the algorithm to a Nash equilibrium is provided under a set of standard assumptions on the cost functions and the communication graph. The effectiveness of the proposed algorithm is demonstrated via simulation.

35 citations

Journal ArticleDOI
TL;DR: A gossip approach for finding a Nash equilibrium in networked games on graphs, where a player’s cost function may be affected by the actions of any subset of players, is considered.

34 citations

Journal ArticleDOI
TL;DR: A relatively fast algorithm within the framework of inexact-ADMM that requires a communication graph for the information exchange between the players as well as a few mild assumptions on cost functions to reach a Nash equilibrium of the game.

28 citations


Cited by
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Journal ArticleDOI
TL;DR: An asynchronous gossip-based algorithm for finding a Nash equilibrium of a game in a distributed multi-player network designed in such a way that players make decisions based on estimates of the other players' actions obtained from local neighbors is presented.

241 citations

Journal ArticleDOI
TL;DR: An aggregate game is adopted for the modeling and analysis of energy consumption control in smart grid, and it is shown that the players’ actions converge to a neighborhood of the unique Nash equilibrium nonlocally.
Abstract: In this paper, an aggregate game is adopted for the modeling and analysis of energy consumption control in smart grid. Since the electricity users’ cost functions depend on the aggregate energy consumption, which is unknown to the end users, an average consensus protocol is employed to estimate it. By neighboring communication among the users about their estimations on the aggregate energy consumption, Nash seeking strategies are developed. Convergence properties are explored for the proposed Nash seeking strategies. For energy consumption game that may have multiple isolated Nash equilibria, a local convergence result is derived. The convergence is established by utilizing singular perturbation analysis and Lyapunov stability analysis. Energy consumption control for a network of heating, ventilation, and air conditioning systems is investigated. Based on the uniqueness of the Nash equilibrium, it is shown that the players’ actions converge to a neighborhood of the unique Nash equilibrium nonlocally. More specially, if the unique Nash equilibrium is an inner Nash equilibrium, an exponential convergence result is obtained. Energy consumption game with stubborn players is studied. In this case, the actions of the rational players can be driven to a neighborhood of their best response strategies by using the proposed method. Numerical examples are presented to verify the effectiveness of the proposed methods.

224 citations

Journal ArticleDOI
TL;DR: In this paper, a distributed Nash equilibrium seeking strategy is proposed for non-cooperative games with non-quadratic payoffs, where multiple isolated Nash equilibria may coexist in the game.
Abstract: In this paper, Nash equilibrium seeking among a network of players is considered. Different from many existing works on Nash equilibrium seeking in noncooperative games, the players considered in this paper cannot directly observe the actions of the players who are not their neighbors. Instead, the players are supposed to be capable of communicating with each other via an undirected and connected communication graph. By a synthesis of a leader-following consensus protocol and the gradient play, a distributed Nash equilibrium seeking strategy is proposed for the noncooperative games. Analytical analysis on the convergence of the players’ actions to the Nash equilibrium is conducted via Lyapunov stability analysis. For games with nonquadratic payoffs, where multiple isolated Nash equilibria may coexist in the game, a local convergence result is derived under certain conditions. Then, a stronger condition is provided to derive a nonlocal convergence result for the nonquadratic games. For quadratic games, it is shown that the proposed seeking strategy enables the players’ actions to converge to the Nash equilibrium globally under the given conditions. Numerical examples are provided to verify the effectiveness of the proposed seeking strategy.

216 citations

Journal ArticleDOI
TL;DR: This paper proposes an augmented gradient-play dynamics with correction, in which players communicate locally only with their neighbors to compute an estimate of the other players’ actions, and exploits incremental passivity properties and shows that a synchronizing, distributed Laplacian feedback can be designed using relative estimates of the neighbors.
Abstract: In this paper, we consider the problem of distributed Nash equilibrium (NE) seeking over networks, a setting in which players have limited local information on the others’ decisions. We start from a continuous-time gradient-play dynamics that converges to an NE under strict monotonicity of the pseudogradient and assumes perfect information. We consider how to modify it in the case of partial, or networked information between players. We propose an augmented gradient-play dynamics with correction, in which players communicate locally only with their neighbors to compute an estimate of the other players’ actions. We derive the new dynamics based on the reformulation as a multiagent coordination problem over an undirected graph. We exploit incremental passivity properties and show that a synchronizing, distributed Laplacian feedback can be designed using relative estimates of the neighbors. Under a strict monotonicity property of the pseudogradient, we show that the augmented gradient-play dynamics converges to consensus on the NE of the game. We further discuss two cases that highlight the tradeoff between properties of the game and the communication graph.

185 citations

Journal ArticleDOI
TL;DR: The convergence of the non-smooth algorithm for the distributed game is proved by taking advantage of its special structure and also combining the techniques of the variational inequality and Lyapunov function.

181 citations