4 papers
Strategically Robust Multi-Agent Reinforcement Learning with Linear Function Approximation
Jake Gonzales, Max Horwitz, Eric Mazumdar +1
Provably efficient and robust equilibrium computation in general-sum Markov games remains a core challenge in multi-agent reinforcement learning. Nash equilibrium is computationall…
Monotone Multispecies Flows
Lauren Conger, Franca Hoffmann, Eric Mazumdar +1
We present a novel notion of -monotonicity for an -species system of partial differential equations governed by mass-preserving flow dynamics, extending monotonicity in Banac…
Coupled Wasserstein Gradient Flows for Min-Max and Cooperative Games
Lauren Conger, Franca Hoffmann, Eric Mazumdar +1
We propose a framework for two-player infinite-dimensional games with cooperative or competitive structure. These games take the form of coupled partial differential equations in w…
Follower Agnostic Methods for Stackelberg Games
Chinmay Maheshwari, James Cheng, S. Shankar Sasty +2
In this paper, we present an efficient algorithm to solve online Stackelberg games, featuring multiple followers, in a follower-agnostic manner. Unlike previous works, our approach…