[22] C. Daskalakis and I. Panageas, "The limit points of (optimistic) gradient descent in min-max optimization," in Advances in Neural Information Processing Systems (NeurIPS), 2018.
[23] T. Başar, “Relaxation techniques and asynchronous algorithms for on-line computation of non-cooperative equilibria,” Journal of Economic Dynamics and Control, vol. 11, no. 4, pp. 531–549, 1987.
[24] J. Conlisk, "Adaptation in games: Two solutions to the Crawford puzzle," Journal of Economic Behavior & Organization, vol. 22, no. 1, pp. 25-50, 1993.
[25] S. Flam and J. Morgan, “Newtonian mechanics and Nash play,” International Game Theory Review, vol. 06, 07 2003.
[26] R. Laraki and P. Mertikopoulos, “Higher order game dynamics,” Journal of Economic Theory, vol. 148, pp. 2666–2695, 06 2013.
[27] B. Gao and L. Pavel, "On passivity, reinforcement learning and higher order learning in multiagent finite games," IEEE Transactions on Automatic Control, vol. 66, no. 1, pp. 121-136, 2021.
[28] S.-H. Wang and E. Davison, "On the stabilization of decentralized control systems," IEEE Transactions on Automatic Control, vol. 18, no. 5, pp. 473-478, 1973.
[29] E. Davison and T. Chang, "Decentralized stabilization and pole assignment for general proper systems," IEEE Transactions on Automatic Control, vol. 35, no. 6, pp. 652-664, 1990.
[30] A. M. Krall, "An extension and proof of the root-locus method," Journal of the Society for Industrial and Applied Mathematics, vol. 9, no. 4, pp. 644–653, 1961.
[31] A. M. Krall, “The root locus method: A survey,” SIAM Review, vol. 12, no. 1, pp. 64–72, 1970.
[32] G. Arslan and J. S. Shamma, "Anticipatory learning in general evolutionary games," in Proceedings of the 45th IEEE Conference on Decision and Control, pp. 6289-6294, 2006.
[33] V. Syrgkanis, A. Agarwal, H. Luo, and R. E. Schapire, "Fast convergence of regularized learning in games," in Advances in Neural Information Processing Systems (C. Cortes, N. Lawrence, D. Lee, M. Sugiyama, and R. Garnett, eds.), vol. 28, Curran Associates, Inc., 2015.
[34] X. Chen and B. Peng, "Hedging in games: Faster convergence of external and swap regrets," in Advances in Neural Information Processing Systems (H. Larochelle, M. Ranzato, R. Hadsell, M. Balcan, and H. Lin, eds.), vol. 33, pp. 18990-18999, Curran Associates, Inc., 2020.
[35] C. Daskalakis, M. Fishelson, and N. Golowich, "Near-optimal no-regret learning in general games," in Advances in Neural Information Processing Systems (M. Ranzato, A. Beygelzimer, Y. Dauphin, P. Liang, and J. W. Vaughan, eds.), vol. 34, pp. 27604-27616, Curran Associates, Inc., 2021.
[36] J. Jordan, “Three problems in learning mixed-strategy Nash equilibria,” Games and Economic Behavior, vol. 5, no. 3, pp. 368–386, 1993.
[37] D. Youla, J. Bongiorno, and C. Lu, "Single-loop feedback-stabilization of linear multivariable dynamical plants," Automatica, vol. 10, no. 2, pp. 159-173, 1974.
[38] M. J. Fox and J. S. Shamma, "Population games, stable games, and passivity," Games, vol. 4, no. 4, pp. 561-583, 2013.
[39] M. Arcak and N. C. Martins, "Dissipativity tools for convergence to Nash equilibria in population games," IEEE Transactions on Control of Network Systems, vol. 8, no. 1, pp. 39-50, 2021.
[40] L. Pavel, "Dissipativity theory in game theory: On the role of dissipativity and passivity in Nash equilibrium seeking," IEEE Control Systems Magazine, vol. 42, no. 3, pp. 150-164, 2022.
[41] J. P. Hespanha, Linear Systems Theory: Second Edition. Princeton University Press, 2018.
[42] W. J. Rugh, Linear System Theory. Prentice Hall, 1996.