20260706:新增一些文章
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concepts/real-world-rl.md
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title: "Real-World RL(真机强化学习)"
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created: 2026-06-29
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updated: 2026-06-29
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type: concept
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tags: [reinforcement-learning, robotics, safety, embodied-intelligence]
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sources: [[real-world-safe-exploration-see-2026]]
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confidence: high
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---
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# Real-World RL(真机强化学习)
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> [[reinforcement-learning|强化学习]] 在**物理世界真实环境**中的直接训练范式。与仿真训练的本质区别:**没有"重来"按钮**,每次交互都可能有真实代价。
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## 与仿真训练的对立
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| 维度 | 仿真训练 | 真机 RL |
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|------|---------|---------|
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| 试错成本 | 近乎零 | 机器损坏 / 人员伤亡 |
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| 数据效率 | 可无限采样 | 每次交互昂贵 |
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| 安全机制 | 可选 | **绝对必需** |
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| 动力学精度 | 受仿真器 fidelity 限制 | 天然精确 |
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## 核心挑战
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[[safe-exploration|安全探索]] 是真机 RL 的首要难题——不仅最终策略要安全,**整个训练过程的每一刻都不能违反安全约束**。
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## 两种训练模式
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- **OTOI**(Offline Training, Online Implementation):仿真训练 → 线上部署,无需安全探索
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- **SOTI**(Simultaneous Online Training and Implementation):边训练边部署,**必须安全探索**
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大多数真实机器人/自动驾驶场景只能走 SOTI 路线。
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## 相关概念
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- [[safe-exploration|安全探索]]
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- [[safe-equilibrium-exploration|SEE 论文]]
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- [[feasible-zone|可行域]]
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- [[reinforcement-learning|强化学习]]
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