A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation

Neural Information Processing Systems 

As one of the most mainstream paradigms for sequential decision-making, RL has extensive applications in many real-world problems (Kober et al., 2013; Mnih et al.,

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