An inexact augmented Lagrangian method with projected Q-ascent yields global last-iterate convergence guarantees for constrained MDP policy optimization, extending from tabular to log-linear and non-linear policies.
This assumption is common in the analysis of PG methods with function approximation [Asad et al., 2024, Agarwal et al., 2021, Yuan et al., 2022b, Ding et al., 2023]
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Augmented Lagrangian Method for Last-Iterate Convergence for Constrained MDPs
An inexact augmented Lagrangian method with projected Q-ascent yields global last-iterate convergence guarantees for constrained MDP policy optimization, extending from tabular to log-linear and non-linear policies.