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A Smooth Polynomial Lyapunov Certificate for Convergence of Q-Learning and Its Smooth Variants
Classical convergence analyses of Q-learning rely on the $\infty$-norm contraction of Bellman operators, and existing ordinary differential equation (ODE) arguments often use the non-differentiable $\infty$-norm directly. This paper develops a smooth polynomial Lyapunov-function-based stability cert
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