Multi-Agent Reinforcement Fine-Tuning (MARFT) is a training paradigm that applies reinforcement learning techniques to fine-tune multiple AI agents simultaneously. Unlike traditional single agent reinforcement learning, MARFT focuses on optimizing the collaborative behaviors of agents within a system — ultimately enhancing their ability to work together effectively. This approach may be beneficial in complex environments where coordinated actions among agents are crucial for achieving desired outcomes (paper).
What is multi agent reinforcement fine tuning?

Multi-Agent Reinforcement Fine-Tuning (MARFT)

Bi-weekly AI Research Paper Readings
Stay on top of emerging trends and frameworks.