How can LLMs help agents communicate in ad-hoc teams?
Language Grounded Multi-agent Communication for Ad-hoc Teamwork
September 27, 2024
https://arxiv.org/pdf/2409.17348This research proposes a new method called "LangGround" to improve communication between AI agents in collaborative tasks, making it understandable to humans.
The key points for LLM-based multi-agent systems:
- Human-interpretable communication: LangGround trains AI agents to communicate using human-like language, making their interactions interpretable to humans.
- Grounding with LLM data: The training uses data from LLM agents skilled in teamwork and communication to guide the AI agents' language development.
- Zero-shot generalization: The trained agents can understand and use language for situations they haven't encountered before, enabling flexibility in new tasks and with new teammates.
- Ad-hoc teamwork: The research demonstrates successful collaboration between independently trained AI agents and LLM agents in scenarios requiring coordination and communication.