Convergence of Heterogeneous Learning Dynamics in Zero-sum Stochastic Games
Published in IEEE-TAC, 2025
This paper presents new families of algorithms for the repeated play of two-agent (near) zero-sum games and two-agent zero-sum stochastic games.
Publications
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Strategizing against Q-learners: A Control-theoretical Approach
Published in IEEE L-CSS, 2024
In this paper, we explore the susceptibility of the Q-learning algorithm (a classical and widely used reinforcement learning method) to strategic manipulation of sophisticated opponents in games.