Traditional Reinforcement Learning (REINFORCE) failed because the gradients had a low signal-to-noise ratio due to binary rewards and weak parameter coupling.
大多数人认为强化学习是解决复杂协调问题的理想方法，但作者明确指出传统RL方法在此类问题上完全失败，挑战了RL在AI协调中的主流应用。
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