YOLO-MARL: Enhancing Multi-agent Reinforcement Learning with LLMs

[cbaracho200]

Summary

This issue discusses the YOLO-MARL framework, which leverages LLMs for high-level task planning to improve policy learning in multi-agent reinforcement learning (MARL). The framework aims to enhance coordination among agents in cooperative games.

Implementation Guidance

• Explore the YOLO-MARL framework and its application in MARL environments.
• Evaluate the effectiveness of using LLMs for strategy generation and planning in MARL.
• Compare YOLO-MARL with traditional MARL algorithms in terms of performance and computational efficiency.

Reference

YOLO-MARL: You Only LLM Once for Multi-agent Reinforcement Learning

Tags

• LLM
• Multi-agent Systems
• Reinforcement Learning

Assignee

composiohq