  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.
