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A self-reinforcing instability trap in Deep Q-learning can be effectively mitigated through controlled bootstrapping and ensemble quantile estimation, leading to more stable training outcomes.
Forget rigid physics engines, this badminton RL environment uses real player data to simulate realistic rallies and strategic gameplay.
