为了全面介绍这一新兴课题的技术内容和现状,Lilian Weng 的这篇文章《LLM Powered Autonomous Agents》对使用 LLM 搭建自治智能代理进行了系统性的总结和讨论。文章概述了构建这类系统的总体架构,以及在规划、记忆和工具使用几大方面的最新研究进展。同时,文章也分析了目前面临的主要挑战,并给出了一些应用案例。本文将...
LLM-powered Autonomous Agents". Lil’Log. lilianweng.github.io/po. Translated by: Sheyang,Wang.(July 2023). 为什么要翻译这篇blog: 随着chatgpt提供的plugin和function call功能出现,激发了大家对LLM作为智能中枢架构的思考。microsoft、google基于LLM发布的copilot架构的应用程序之前陆续推出时,也是引发大家...
LLM-powered autonomous agents are evolving beyond single agents and static multi-agent systems with the emergence of frameworks like Autogen and CrewAI. This technique allows developers [...]
To overcome these drawbacks, the research team from Microsoft suggested TaskWeaver, a code-first framework for creating LLM-powered autonomous agents. TaskWeaver’s unique feature is its ability to treat user-defined plugins as callable functions, converting e...
🔥 [Jul 2023] "WebArena: A Realistic Web Environment for Building Autonomous Agents." Shuyan Zhou (CMU) et al. arXiv. [paper] [code] [project page] [Jul 2023] "A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis." Izzeddin Gur (DeepMind) et al. ...
ChatDev: Collaborative AI agents for software development. XAgent: An Autonomous LLM Agent for Complex Task Solving. EasyRL4Rec: A user-friendly RL library for recommender systems. 📊 Citation @misc{luo2024repoagent,title={RepoAgent: An LLM-Powered Open-Source Framework for Repository-level Cod...
Recent studies show that collaborating multiple large language model (LLM) powered agents is a promising way for task solving. However, current approaches are constrained by using a fixed number of agents and static communication structures. In this work, we propose automatically selecting a team of...
Barbara,Hayes-RothPatrick,Doyle - 《Autonomous Agents & Multi Agent Systems》 被引量: 55发表: 1998年 Measurement and Evaluation of Embodied Conversational Agents In this [book] chapter, we cover four main topics. First, we consider the overall questions of evaluating interactive systems. Second, ...
随着诸如 Autogen 和 CrewAI 等框架的出现, LLM 驱动的自主代理 正在超越单一代理和静态的多代理系统。这项技术允许开发人员将复杂的任务分解为多个小任务,再交由不同角色的代理完成。开发人员可以使用预配置的工具来执行任务,代理之间通过对话来协调任务流程。该技术仍
Fig. 1. Overview of a LLM-powered autonomous agent system. 组件一:规划 一个复杂的任务通常涉及许多步骤。代理需要知道它们是什么并提前计划。 任务分解 Chain of Thought (CoT; Wei等,2022)已经成为增强模型在复杂任务上性能的标准提示词技术。该模型被指示“逐步思考”,利用更多的测试时间计算来将困难的任务...