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Update 强化学习.md #13

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3 changes: 2 additions & 1 deletion docs/强化学习.md
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Expand Up @@ -62,7 +62,8 @@

### DQN的两个关键trick分别是什么？

- [ ] TODO
- Replay buffer: 经验回放，训练过程中从经验池中随机采样更新网络参数，一方面打破样本相关性，另一方面提高样本效率（一个样本可能多次参与网络参数更新）
- Fixed Q-targets: 在更新Q网络参数时，用以计算$q_{target}$的网络参数是上一次迭代前的网络参数$\theta_{i-1}$，当前q值是根据网络参数为$\theta_{i}$的Q网络得出，这也是一种打乱相关性的机理。

### DQN 都有哪些变种？DQN有哪些改进方向？

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