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4 papers
Toward a Unified Lyapunov-Certified ODE Convergence Analysis of Smooth Q-Learning with p-Norms
Donghwan Lee, Hyunjun Na
Convergence of Q-learning has been the subject of extensive study for decades. Among the available techniques, the ordinary differential equation (ODE) method is particularly appea…
R-GTD: A Geometric Analysis of Gradient Temporal-Difference Learning in Singular Regimes
Hyunjun Na, Donghwan Lee
Gradient temporal-difference (GTD) learning algorithms are widely used for off-policy policy evaluation with function approximation. However, existing convergence analyses rely on…
Soft Deterministic Policy Gradient with Gaussian Smoothing
Hyunjun Na, Donghwan Lee
Deterministic policy gradient (DPG) is widely utilized for continuous control; however, it inherently relies on the differentiability of the critic with respect to the action durin…
Finite-Time Analysis of Simultaneous Double Q-learning
Hyunjun Na, Donghwan Lee
-learning is one of the most fundamental reinforcement learning (RL) algorithms. Despite its widespread success in various applications, it is prone to overestimation bias in th…