  Leveraging large language models (LLMs), autonomous agents have significantly
improved, gaining the ability to handle a variety of tasks. In open-ended
settings, optimizing collaboration for efficiency and effectiveness demands
flexible adjustments. Despite this, current research mainly emphasizes fixed,
task-oriented workflows and overlooks agent-centric organizational structures.
Drawing inspiration from human organizational behavior, we introduce a
self-organizing agent system (S-Agents) with a "tree of agents" structure for
dynamic workflow, an "hourglass agent architecture" for balancing information
priorities, and a "non-obstructive collaboration" method to allow asynchronous
task execution among agents. This structure can autonomously coordinate a group
of agents, efficiently addressing the challenges of open and dynamic
environments without human intervention. Our experiments demonstrate that
S-Agents proficiently execute collaborative building tasks and resource
collection in the Minecraft environment, validating their effectiveness.
