S-Agents: Self-organizing Agents in Open-ended Environments
<|reference_start|>S-Agents: Self-organizing Agents in Open-ended Environments: 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.<|reference_end|>
@article{chen2024s-agents:,
    title={S-Agents: Self-organizing Agents in Open-ended Environments},
    author={Jiaqi Chen and Yuxian Jiang and Jiachen Lu and Li Zhang},
    journal={arXiv preprint arXiv:2402.04578},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.04578},
    primaryClass={cs.AI cs.MA}
}