新闻
Introducing Feedback Delays to Non-Delayed Adversarial MDPs: Optimal $\sqrt S$ and $\sqrt K$ Dependencies in Tabular and Linear AMDPs
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- Researchers resolved a long-standing open problem in adversarial MDPs by achieving optimal regret bounds using a technique that intentionally introduces feedback delays during learning.
- 为何重要
- Matters for engineers building reinforcement learning systems that must handle adversarial environments with delayed or asynchronous feedback from changing policies.
- 注意
- Results are theoretical with polynomial dependencies on problem dimensions; practical applicability and computational overhead of the Geometric Resampling with Rejection method remain unclear.
- lora
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