[2024 Best AI Paper] SelfGoal: Your Language Agents Already Know How to Achieve High-level Goals
Автор: Paper With Video
Загружено: 2024-10-18
Просмотров: 7
This video was created using https://paperspeech.com. If you’d like to create explainer videos for your own papers, please visit the website!
Title: SelfGoal: Your Language Agents Already Know How to Achieve High-level Goals
Authors: Ruihan Yang, Jiangjie Chen, Yikai Zhang, Siyu Yuan, Aili Chen, Kyle Richardson, Yanghua Xiao, Deqing Yang
Abstract:
Language agents powered by large language models (LLMs) are increasingly
valuable as decision-making tools in domains such as gaming and programming.
However, these agents often face challenges in achieving high-level goals
without detailed instructions and in adapting to environments where feedback is
delayed. In this paper, we present SelfGoal, a novel automatic approach
designed to enhance agents' capabilities to achieve high-level goals with
limited human prior and environmental feedback. The core concept of SelfGoal
involves adaptively breaking down a high-level goal into a tree structure of
more practical subgoals during the interaction with environments while
identifying the most useful subgoals and progressively updating this structure.
Experimental results demonstrate that SelfGoal significantly enhances the
performance of language agents across various tasks, including competitive,
cooperative, and deferred feedback environments. Project page:
https://selfgoal-agent.github.io.
![[2024 Best AI Paper] SelfGoal: Your Language Agents Already Know How to Achieve High-level Goals](https://ricktube.ru/thumbnail/i3tlQt5lBSU/hq720.jpg)
Доступные форматы для скачивания:
Скачать видео mp4
-
Информация по загрузке: