面向开放式多智能体导航的分层自动组织系统
Hierarchical Auto-Organizing System for Open-Ended Multi-Agent Navigation
AI总结：
针对Minecraft开放世界中的多智能体导航挑战，提出HAS分层自动组织系统，实现集中规划与分散执行、动态组调整及多模态感知，以完成搜索和探索任务。
摘要：
由于开放世界环境的动态性和不可预测性，在Minecraft中导航复杂环境对多智能体系统构成了重大挑战。智能体必须与环境交互，并与其他智能体协调行动以实现共同目标。然而，传统方法往往难以有效管理智能体间的通信和任务分配，而这些对于有效的多智能体导航至关重要。此外，处理和整合多模态信息（如视觉、文本和听觉数据）对于智能体理解其目标并成功、完整地导航环境是必不可少的。为解决这一问题，我们设计了HAS框架，以自动组织基于LLM的智能体组来完成导航任务。在我们的方法中，我们设计了一个分层自动组织导航系统，其特点包括：1）用于多智能体组织的分层系统，确保集中规划与分散执行；2）自动组织和内部通信机制，能够在子任务下动态调整组；3）多模态信息平台，促进多模态感知，以用一个系统执行三项导航任务。为了评估组织行为，我们在Minecraft环境中设计了一系列导航任务，包括搜索和探索。我们旨在开发具身组织，推动具身AI的边界，使其朝着更接近人类组织结构的形态发展。
英文摘要：
Due to the dynamic and unpredictable open-world setting, navigating complex environments in Minecraft poses significant challenges for multi-agent systems. Agents must interact with the environment and coordinate their actions with other agents to achieve common objectives. However, traditional approaches often struggle to efficiently manage inter-agent communication and task distribution, crucial for effective multi-agent navigation. Furthermore, processing and integrating multi-modal information (such as visual, textual, and auditory data) is essential for agents to comprehend their goals and navigate the environment successfully and fully. To address this issue, we design the HAS framework to auto-organize groups of LLM-based agents to complete navigation tasks. In our approach, we devise a hierarchical auto-organizing navigation system, which is characterized by 1) a hierarchical system for multi-agent organization, ensuring centralized planning and decentralized execution; 2) an auto-organizing and intra-communication mechanism, enabling dynamic group adjustment under subtasks; 3) a multi-modal information platform, facilitating multi-modal perception to perform the three navigation tasks with one system. To assess organizational behavior, we design a series of navigation tasks in the Minecraft environment, which includes searching and exploring. We aim to develop embodied organizations that push the boundaries of embodied AI, moving it towards a more human-like organizational structure.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
