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cs.GT2024
Learning Equilibria in Adversarial Team Markov Games: A Nonconvex-Hidden-Concave Min-Max Optimization Problem
Fivos Kalogiannis, Jingming Yan, Ioannis Panageas
We study the problem of learning a Nash equilibrium (NE) in Markov games which is a cornerstone in multi-agent reinforcement learning (MARL). In particular, we focus on infinite-ho…
cs.GT2024
Computing Nash Equilibria in Potential Games with Private Uncoupled Constraints
Nikolas Patris, Stelios Stavroulakis, Fivos Kalogiannis +2
We consider the problem of computing Nash equilibria in potential games where each player's strategy set is subject to private uncoupled constraints. This scenario is frequently en…