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Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic under Markovian Sampling with Neural Network Parametrization
The current state-of-the-art theoretical analysis of Actor-Critic (AC) algorithms significantly lags in addressing the practical aspects of AC implementations.
On the Global Convergence of Natural Actor-Critic with Two-layer Neural Network Parametrization
To achieve that, we propose a Natural Actor-Critic algorithm with 2-Layer critic parametrization (NAC2L).
On the Global Convergence of Fitted Q-Iteration with Two-layer Neural Network Parametrization
Deep Q-learning based algorithms have been applied successfully in many decision making problems, while their theoretical foundations are not as well understood.
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