干的像沙漠般的一篇，关于 RL Terms.
RL 术语很多，且不好理解，例如:
policy, state, action
rewardreturn, value, advantage
baseline, TD error, GAE
clipping, KL
这篇用一个例子把 RL 的术语写给 LLM 读者 （依然太干了，RL 真的很难写得生动有趣）
Dongxi NLP explains RL terms like policy, advantage, and GAE through one example
AIDongxi NLP says reinforcement learning jargon is hard to follow and presents a single worked example to explain terms including policy, state, action, reward, return, value, advantage, baseline, TD error, GAE, clipping, and KL for LLM readers. The post calls its own writing dry and says RL is hard to make lively.
Dongxi NLPVerified on X
@dongxi_nlp
https://x.com/i/article/2115385031132635138View quoted post on X