Guo-Xin Wang

G2MAF: Test-Time Gradient Guidance for Multi-Agent Flow Policies

Offline multi-agent reinforcement learning (MARL) learns cooperative policies from fixed datasets without further environment interaction and a learned policy is frozen at deployment. Such a frozen policy typically proposes a single joint action and executes it directly at deployment time. However, this one-shot deploy...