A Lyra tutorial https://dev.epicgames.com/community/learning/tutorials/MWLq/unreal-engine-ue5-lyra-gas-excellent-practice-of-attributeset-i
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LangChain Agent的设计还考虑了泛化能力和Prompt控制,利用大型LLMs的强大few-shot和zero-shot泛化能力,以及Prompt控制的核心基础。这种设计使得LangChain Agent能够在没有大量训练数据的情况下,通过少量的提示就能生成有意义的回答,从而提高了其实用性和效率。 原文链接:https://www.cnblogs.com/xiaoqi/p/18045576/Lang...
and that the planner should act as advocate for a particular group, within a context where planners and their clients were both engaged in a learning ... P,Hall - 《Environment & Planning B Planning & Design》 被引量: 7发表: 1983年 Online goal recognition through mirroring: humans and age...
We demonstrate in addition that nest-tagged views recorded during such simulated learning flights are sufficient for a homing agent to pinpoint the goal, by identifying nest direction when encountering familiar views. We discuss how the information acquired during learning flights close to the nest ...