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Rate-Optimal Algorithm for Adversarial Linear CMDPs

Yu, Kihyun et al.
arXiv (All) · Papers
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machine-learning
We study episodic adversarial linear constrained Markov decision processes (CMDPs) with unknown transitions, where both the loss and constraint functions may vary adversarially across episodes. The best previous algorithm achieves $\widetilde{\mathcal{O}}(K^{3/4})$ regret and cumulative constraint v
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