Projected-gradient algorithms for Generalized Equilibrium seeking in Aggregative Games arepreconditioned Forward-Backward methods

We show that projected-gradient methods for the distributed computation of generalized Nash equilibria in ag- gregative games are preconditioned forward-backward splitting methods appliedto the KKT operator of the game. Specifically, we adopt the preconditioned forward-backward design, recently conceived by Yi and Pavel in the manuscript ’’A distributed primal-dual algorithm for computation of generalized Nash equilibria via operator splitting methods’’ for generalized Nash equilibrium seeking in aggregative games. Consequently, we notice that two projected-gradient methods recently proposed in the literature are preconditioned forward-backward meth- ods. More generally, we provide a unifying operator-theoretic ground to design projected-gradient methods for generalized equilibrium seeking in aggregative games.

[1]  Francisco Facchinei,et al.  Generalized Nash Equilibrium Problems , 2010, Ann. Oper. Res..

[2]  Walid Saad,et al.  Game Theoretic Methods for the Smart Grid , 2012, ArXiv.

[3]  Sergio Grammatico,et al.  Semi-Decentralized Nash Equilibrium Seeking in Aggregative Games With Separable Coupling Constraints and Non-Differentiable Cost Functions , 2017, IEEE Control Systems Letters.

[4]  Heinz H. Bauschke,et al.  Convex Analysis and Monotone Operator Theory in Hilbert Spaces , 2011, CMS Books in Mathematics.

[5]  Marc Teboulle,et al.  Lagrangian Duality and Related Multiplier Methods for Variational Inequality Problems , 1999, SIAM J. Optim..

[6]  Sergio Grammatico,et al.  Opinion dynamics are proximal dynamics in multi-agent network games , 2017, 2017 IEEE 56th Annual Conference on Decision and Control (CDC).

[7]  Francesca Parise,et al.  A Mean Field control approach for demand side management of large populations of Thermostatically Controlled Loads , 2015, 2015 European Control Conference (ECC).

[8]  Jorge Barrera,et al.  Dynamic Incentives for Congestion Control , 2015, IEEE Transactions on Automatic Control.

[9]  Shu Liang,et al.  Distributed Nash equilibrium seeking for aggregative games with coupled constraints , 2016, Autom..

[10]  Sergio Grammatico,et al.  Proximal Dynamics in Multiagent Network Games , 2018, IEEE Transactions on Control of Network Systems.

[11]  Munther A. Dahleh,et al.  Demand Response Using Linear Supply Function Bidding , 2015, IEEE Transactions on Smart Grid.

[12]  Lacra Pavel,et al.  An extension of duality to a game-theoretic framework , 2007, Autom..

[13]  Ankur A. Kulkarni,et al.  On the variational equilibrium as a refinement of the generalized Nash equilibrium , 2012, Autom..

[14]  P. L. Combettes,et al.  Compositions and convex combinations of averaged nonexpansive operators , 2014, 1407.5100.

[15]  P. L. Combettes,et al.  Variable metric forward–backward splitting with applications to monotone inclusions in duality , 2012, 1206.6791.

[16]  F. Facchinei,et al.  Finite-Dimensional Variational Inequalities and Complementarity Problems , 2003 .

[17]  Angelia Nedic,et al.  Distributed Algorithms for Aggregative Games on Graphs , 2016, Oper. Res..

[18]  Nikolai S. Kukushkin,et al.  Best response dynamics in finite games with additive aggregation , 2004, Games Econ. Behav..

[19]  Francesca Parise,et al.  Distributed computation of generalized Nash equilibria in quadratic aggregative games with affine coupling constraints , 2016, 2016 IEEE 55th Conference on Decision and Control (CDC).

[20]  Farzad Salehisadaghiani,et al.  Distributed Nash equilibrium seeking: A gossip-based algorithm , 2016, Autom..

[21]  Lacra Pavel,et al.  A distributed primal-dual algorithm for computation of generalized Nash equilibria via operator splitting methods , 2017, 2017 IEEE 56th Annual Conference on Decision and Control (CDC).

[22]  Sergio Grammatico Dynamic Control of Agents Playing Aggregative Games With Coupling Constraints , 2016, IEEE Transactions on Automatic Control.

[23]  Francesca Parise,et al.  Mean field constrained charging policy for large populations of Plug-in Electric Vehicles , 2014, 53rd IEEE Conference on Decision and Control.

[24]  Ian A. Hiskens,et al.  Efficient decentralized coordination of large-scale plug-in electric vehicle charging , 2016, Autom..

[25]  Yonina C. Eldar,et al.  Convex Optimization in Signal Processing and Communications , 2009 .

[26]  Francesca Parise,et al.  Decentralized Convergence to Nash Equilibria in Constrained Deterministic Mean Field Control , 2014, IEEE Transactions on Automatic Control.

[27]  Sergio Grammatico,et al.  On convexity and monotonicity in generalized aggregative games , 2017 .