智能体的互联网：编织异构智能体的协作智能网络

Internet of Agents: Weaving a Web of Heterogeneous Agents for Collaborative Intelligence

July 9, 2024

作者: Weize Chen, Ziming You, Ran Li, Yitong Guan, Chen Qian, Chenyang Zhao, Cheng Yang, Ruobing Xie, Zhiyuan Liu, Maosong Sun

cs.AI

摘要

大型语言模型（LLMs）的快速发展为高度能力的自主代理的发展铺平了道路。然而，现有的多代理框架往往在整合不同能力的第三方代理方面遇到困难，因为它们依赖于在其自身生态系统中定义的代理。它们还面临着在模拟分布式环境方面的挑战，因为大多数框架仅限于单设备设置。此外，这些框架通常依赖于硬编码的通信管道，限制了它们对动态任务需求的适应性。受互联网概念启发，我们提出了代理互联网（IoA），这是一个通过提供灵活且可扩展的平台来解决这些限制的新型框架，用于基于LLM的多代理协作。IoA引入了代理集成协议、类似即时通讯的架构设计以及用于代理组建和对话流控制的动态机制。通过对一般助理任务、具身人工智能任务和检索增强生成基准的广泛实验，我们证明IoA始终优于最先进的基准线，展示了它促进异构代理之间有效协作的能力。IoA代表了迈向在类似互联网环境中连接不同代理的一步，代理可以无缝协作以实现更高的智能和能力。我们的代码库已发布在https://github.com/OpenBMB/IoA。

English

The rapid advancement of large language models (LLMs) has paved the way for the development of highly capable autonomous agents. However, existing multi-agent frameworks often struggle with integrating diverse capable third-party agents due to reliance on agents defined within their own ecosystems. They also face challenges in simulating distributed environments, as most frameworks are limited to single-device setups. Furthermore, these frameworks often rely on hard-coded communication pipelines, limiting their adaptability to dynamic task requirements. Inspired by the concept of the Internet, we propose the Internet of Agents (IoA), a novel framework that addresses these limitations by providing a flexible and scalable platform for LLM-based multi-agent collaboration. IoA introduces an agent integration protocol, an instant-messaging-like architecture design, and dynamic mechanisms for agent teaming and conversation flow control. Through extensive experiments on general assistant tasks, embodied AI tasks, and retrieval-augmented generation benchmarks, we demonstrate that IoA consistently outperforms state-of-the-art baselines, showcasing its ability to facilitate effective collaboration among heterogeneous agents. IoA represents a step towards linking diverse agents in an Internet-like environment, where agents can seamlessly collaborate to achieve greater intelligence and capabilities. Our codebase has been released at https://github.com/OpenBMB/IoA.