In the literature on game-theoretic equilibrium finding, focus has mainly been on solving a
single game in isolation. In practice, however, strategic interactions--ranging from routing …

We propose a new method called the Metropolis-adjusted Mirror Langevin algorithm for
approximate sampling from distributions whose support is a compact and convex set. This …

Motivated by alternating game-play in two-player games, we study an altenating variant of
the\textit {Online Linear Optimization}(OLO). In alternating OLO, a\textit {learner} at each …

Recent advances in quantum computing and in particular, the introduction of quantum
GANs, have led to increased interest in quantum zero-sum game theory, extending the …

A celebrated result in the interface of online learning and game theory guarantees that the
repeated interaction of no-regret players leads to a coarse correlated equilibrium (CCE)--a …

Characterizing the performance of no-regret dynamics in multi-player games is a
foundational problem at the interface of online learning and game theory. Recent results …

We study online learning and equilibrium computation in games with polyhedral decision
sets, a property shared by normal-form games (NFGs) and extensive-form games (EFGs) …

We study two variants of the mirror descent-ascent algorithm for solving min-max problems
on the space of measures: simultaneous and sequential. We work under assumptions of …

We investigate the accuracy of prediction in deterministic learning dynamics of zero-sum
games with random initializations, specifically focusing on observer uncertainty and its …

Decision-making problems, categorized as single-agent, eg, Atari, cooperative multi-agent,
eg, Hanabi, competitive multi-agent, eg, Hold'em poker, and mixed cooperative and …