Enhancing Collaboration with LLMs

This paper studies the use of large language models to facilitate consensus among various agents, demonstrating a vital technique for improving collaboration in multi-agent systems. A thorough analysis helps understand the behavior of agents when guided by LLMs in reaching a consensus for complex tasks.

• Investigated LLM-driven strategies for consensus.
• Analyzed influences of agent number and network topology.
• Demonstrated LLM application in multi-robot aggregation.

As we explore the capabilities of LLMs in automating and harmonizing efforts, such research sets the stage for expansive development and utilization of AI in coordination-intensive scenarios.