6 citations · 12 across the 16 of their papers we have counts for
4 papers · 1 filter
Optimistic Policy Gradient in Multi-Player Markov Games with a Single Controller: Convergence Beyond the Minty Property
Ioannis Anagnostides, Ioannis Panageas, Gabriele Farina +1
Policy gradient methods enjoy strong practical performance in numerous tasks in reinforcement learning. Their theoretical understanding in multiagent settings, however, remains lim…
Zero-sum Polymatrix Markov Games: Equilibrium Collapse and Efficient Computation of Nash Equilibria
Fivos Kalogiannis, Ioannis Panageas
The works of (Daskalakis et al., 2009, 2022; Jin et al., 2022; Deng et al., 2023) indicate that computing Nash equilibria in multi-player Markov games is a computationally hard tas…
On the Convergence of No-Regret Learning Dynamics in Time-Varying Games
Ioannis Anagnostides, Ioannis Panageas, Gabriele Farina +1
Most of the literature on learning in games has focused on the restrictive setting where the underlying repeated game does not change over time. Much less is known about the conver…
Algorithms and Complexity for Computing Nash Equilibria in Adversarial Team Games
Ioannis Anagnostides, Fivos Kalogiannis, Ioannis Panageas +2
Adversarial team games model multiplayer strategic interactions in which a team of identically-interested players is competing against an adversarial player in a zero-sum game. Suc…