Unified ODE convergence analysis for smooth Q-learning variants via p-norm Lyapunov functions, valid even when the Bellman operator is not a contraction.
In addition, there exists a constant C0 < ∞ such that for any initial θ0 ∈ Rn, we have E[∥εk+1∥2 2|Gk] ≤ C0(1 + ∥θk∥2 2), ∀k ≥ 0 with probability one
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Toward a Unified Lyapunov-Certified ODE Convergence Analysis of Smooth Q-Learning with p-Norms
Unified ODE convergence analysis for smooth Q-learning variants via p-norm Lyapunov functions, valid even when the Bellman operator is not a contraction.