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cs.GT2025

Robust equilibria in continuous games: From strategic to dynamic robustness

Kyriakos Lotidis, Panayotis Mertikopoulos, Nicholas Bambos +1

In this paper, we examine the robustness of Nash equilibria in continuous games, under both strategic and dynamic uncertainty. Starting with the former, we introduce the notion of…

cs.GT2025

Multi-agent learning under uncertainty: Recurrence vs. concentration

Kyriakos Lotidis, Panayotis Mertikopoulos, Nicholas Bambos +1

In this paper, we examine the convergence landscape of multi-agent learning under uncertainty. Specifically, we analyze two stochastic models of regularized learning in continuous…

cs.GT2025

Choose Your Battles: Distributed Learning Over Multiple Tug of War Games

Siddharth Chandak, Ilai Bistritz, Nicholas Bambos

Consider players and games taking place simultaneously. Each of these games is modeled as a Tug-of-War (ToW) game where increasing the action of one player decreases the re…

eess.SY2025

Optimal Control for Remote Patient Monitoring with Multidimensional Health States

Siddharth Chandak, Isha Thapa, Nicholas Bambos +1

Selecting the right monitoring level in Remote Patient Monitoring (RPM) systems for e-healthcare is crucial for balancing patient outcomes, various resources, and patient's quality…

cs.LG2025

Finite-Time Bounds for Two-Time-Scale Stochastic Approximation with Arbitrary Norm Contractions and Markovian Noise

Siddharth Chandak, Shaan Ul Haque, Nicholas Bambos

Two-time-scale Stochastic Approximation (SA) is an iterative algorithm with applications in reinforcement learning and optimization. Prior finite time analysis of such algorithms h…