collaborators

6 papers

cs.GT2026

When and Why is Optimistic Multiplicative Weights Slow? The Geometry of Energy Dissipation

John Lazarsfeld, Anas Barakat, Georgios Piliouras +2

This paper studies the convergence of the Optimistic Multiplicative Weights Update algorithm (OMWU) in two player zero-sum games. Recent works have identified instances on which th…

cs.GT2026

Deep Incentive Design with Differentiable Equilibrium Blocks

Vinzenz Thoma, Georgios Piliouras, Luke Marris

Automated design of multi-agent interactions with desirable equilibrium outcomes is inherently difficult due to the computational hardness, non-uniqueness, and instability of the r…

cs.LG2026

Optimism Without Regularization: Constant Regret in Zero-Sum Games

John Lazarsfeld, Georgios Piliouras, Ryann Sim +1

This paper studies the optimistic variant of Fictitious Play for learning in two-player zero-sum games. While it is known that Optimistic FTRL -- a regularized algorithm with a bou…

cs.LG2025

Online Multi-Agent Control with Adversarial Disturbances

Anas Barakat, John Lazarsfeld, Georgios Piliouras +1

Online multi-agent control problems, where many agents pursue competing and time-varying objectives, are widespread in domains such as autonomous robotics, economics, and energy sy…

cs.GT2025

Solving Zero-Sum Convex Markov Games

Fivos Kalogiannis, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Ian Gemp +1

We contribute the first provable guarantees of global convergence to Nash equilibria (NE) in two-player zero-sum convex Markov games (cMGs) by using independent policy gradient met…

cs.LG2025

Fast and Furious Symmetric Learning in Zero-Sum Games: Gradient Descent as Fictitious Play

John Lazarsfeld, Georgios Piliouras, Ryann Sim +1

This paper investigates the sublinear regret guarantees of two non-no-regret algorithms in zero-sum games: Fictitious Play, and Online Gradient Descent with constant stepsizes. In…