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stat.ML2024
Learning mirror maps in policy mirror descent
Carlo Alfano, Sebastian Towers, Silvia Sapora +2
Policy Mirror Descent (PMD) is a popular framework in reinforcement learning, serving as a unifying perspective that encompasses numerous algorithms. These algorithms are derived t…
stat.ML2023
A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence
Carlo Alfano, Rui Yuan, Patrick Rebeschini
Modern policy optimization methods in reinforcement learning, such as TRPO and PPO, owe their success to the use of parameterized policies. However, while theoretical guarantees ha…