Summary of Embodied Llm Agents Learn to Cooperate in Organized Teams, by Xudong Guo et al.
Embodied LLM Agents Learn to Cooperate in Organized Teams
by Xudong Guo, Kaixuan Huang, Jiale Liu, Wenhui Fan, Natalia Vélez, Qingyun Wu, Huazheng Wang, Thomas L. Griffiths, Mengdi Wang
First submitted to arxiv on: 19 Mar 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL); Computers and Society (cs.CY); 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 This paper introduces a framework for Large Language Models (LLMs) to improve their performance in multi-agent systems. LLMs are highly effective at reasoning and decision-making due to their extensive knowledge base, but they often over-report and comply with instructions, leading to information redundancy and confusion. To address this issue, the authors propose a prompt-based organization structure for LLM agents, inspired by human organizations. The framework is tested through experiments involving embodied LLM agents and human-agent collaboration, which demonstrate the impact of designated leadership on team efficiency. Additionally, the authors harness the potential of LLMs to develop novel organization structures that reduce communication costs and enhance team performance. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine a world where computers can work together like humans do! This paper explores how we can make big computer models (called Large Language Models) work better in teams. Right now, these models are very good at understanding language, but they often get stuck repeating the same information over and over. The authors of this paper came up with a new way to help these models work together more efficiently. They tested their idea by having the computers work with humans on tasks, and it worked! This breakthrough could lead to new ways for computers to collaborate and make our lives easier. |
Keywords
» Artificial intelligence » Knowledge base » Prompt
