Statistical Convergence of Transformer Encoder-Accelerated Robust Reinforcement Learning

Obtaining the optimal action-value function in Markov decision processes is computationally intensive in large state--action spaces. In this study, we present statistically rigorous convergence results for a robust reinforcement learning algorithm warm-started by a transformer-based action-value fun