智能體的網絡：編織異質智能體的網絡以促進協作智能

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

大型語言模型（LLMs）的快速發展為高度能力的自主代理的發展鋪平了道路。然而，現有的多代理框架通常難以整合不同能力的第三方代理，因為它們依賴於在其自身生態系統中定義的代理。它們還面臨著在模擬分佈式環境方面的挑戰，因為大多數框架僅限於單設備設置。此外，這些框架通常依賴於硬編碼的通信管道，限制了它們對動態任務需求的適應能力。受互聯網概念的啟發，我們提出了代理互聯網（IoA），這是一個新穎的框架，通過提供一個靈活且可擴展的平台，用於基於LLM的多代理協作。IoA引入了代理集成協議、即時消息傳遞式的架構設計，以及用於代理組隊和對話流控制的動態機制。通過對一般助理任務、具體化AI任務和檢索增強生成基準的大量實驗，我們展示了IoA始終優於最先進的基準線，展示了其促進異質代理之間有效協作的能力。IoA代表了將不同代理連接在類似互聯網環境中的一步，代理可以無縫協作以實現更大的智能和能力。我們的代碼庫已在https://github.com/OpenBMB/IoA 上發布。

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.