mlsanityData to 7 Oct 2026

Follow-the-Regularized-Leader Routes to Chaos in Routing Games

arXiv 2102.07974 ↗First posted 16 Feb 2021cs.GT cs.LG math.DScited by 9

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Abstract (arXiv)

We study the emergence of chaotic behavior of Follow-the-Regularized Leader (FoReL) dynamics in games. We focus on the effects of increasing the population size or the scale of costs in congestion games, and generalize recent results on unstable, chaotic behaviors in the Multiplicative Weights Update dynamics to a much larger class of FoReL dynamics. We establish that, even in simple linear non-atomic congestion games with two parallel links and any fixed learning rate, unless the game is fully symmetric, increasing the population size or the scale of costs causes learning dynamics to become unstable and eventually chaotic, in the sense of Li-Yorke and positive topological entropy. Furthermore, we show the existence of novel non-standard phenomena such as the coexistence of stable Nash equilibria and chaos in the same game. We also observe the simultaneous creation of a chaotic attractor as another chaotic attractor gets destroyed. Lastly, although FoReL dynamics can be strange and non-equilibrating, we prove that the time average still converges to an exact equilibrium for any choice of learning rate and any scale of costs.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 14 of its 60 references that are in the map. First posted on arXiv 16 Feb 2021.

Builds on

14 of 60 references.

References · 14

  1. 2019Introduction to Online Convex Optimizationcited by 793
  2. 2018Which Training Methods for GANs do actually Converge?cited by 672
  3. 2016Learning in games with continuous action sets and unknown payoff functionscited by 78
  4. 2018The Unusual Effectiveness of Averaging in GAN Trainingcited by 73
  5. 2018Interaction Matters: A Note on Non-asymptotic Local Convergence of Generative Adversarial Networkscited by 68
  6. 2017Gradient descent GAN optimization is locally stablecited by 65
  7. 2020No-regret learning and mixed Nash equilibria: They do not mixcited by 49
  8. 2017Multiplicative Weights Update with Constant Step-Size in Congestion Games: Convergence, Limit Cycles and Chaoscited by 29
  9. 2019Finite Regret and Cycles with Fixed Step-Size via Alternating Gradient Descent-Ascentcited by 28
  10. 2016Riemannian game dynamicscited by 18
  11. 2019Fast and Furious Learning in Zero-Sum Games: Vanishing Regret with Non-Vanishing Step Sizescited by 14
  12. 2019The route to chaos in routing games: When is Price of Anarchy too optimistic?cited by 14
2 more
  1. 2018Hessian barrier algorithms for linearly constrained optimization problemscited by 8
  2. 2018Multiplicative Weights Update as a Distributed Constrained Optimization Algorithm: Convergence to Second-order Stationary Points Almost Alwayscited by 7

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 2; 2023: 1; 2024: 2; 2025: 1; 2026: 2.

9 papers.