Adversarial action removal in self-play RL inflicts greater damage than random masking or learned perturbations, persists across algorithms and domains, transfers between agents, and resists recovery through extended training.
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When Actions Disappear: Adversarial Action Removal in Self-Play Reinforcement Learning
Adversarial action removal in self-play RL inflicts greater damage than random masking or learned perturbations, persists across algorithms and domains, transfers between agents, and resists recovery through extended training.