Unverified50% confidenceFactExact time
Classic multi-armed bandit algorithms (such as ε-greedy) assume that the reward distribution of each arm is independent; when the action space explodes combinatorially and feedback is sparse, the exploration cost of independently evaluating each arm grows linearly with the number of actions, and efficiency drops sharply.
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10/28/2026
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