Summary of S-agents: Self-organizing Agents in Open-ended Environments, by Jiaqi Chen and Yuxian Jiang and Jiachen Lu and Li Zhang
S-Agents: Self-organizing Agents in Open-ended Environments
by Jiaqi Chen, Yuxian Jiang, Jiachen Lu, Li Zhang
First submitted to arxiv on: 7 Feb 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Multiagent Systems (cs.MA)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel approach to autonomous agent collaboration is proposed, which leverages large language models (LLMs) to improve task efficiency and effectiveness in open-ended settings. The current research mainly focuses on fixed workflows and neglects organizational structures for agents. Drawing inspiration from human behavior, the authors introduce a self-organizing agent system (S-Agents) with a “tree of agents” structure, an “hourglass agent architecture,” and a non-obstructive collaboration method for asynchronous task execution. Experimental results demonstrate that S-Agents can efficiently execute collaborative tasks in Minecraft, validating their effectiveness. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Autonomous agents are getting smarter thanks to large language models (LLMs). To make them work together better, we need new ways of organizing them. The current approach focuses on fixed workflows and doesn’t consider how the agents should work together. Inspired by human behavior, researchers have created a system called S-Agents that can adjust its workflow to fit different tasks. It uses a special structure and method for letting agents work together without getting in each other’s way. In a test with Minecraft, the S-Agents were able to work together well and complete tasks efficiently. |
