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...
Guo-Wei Zou, Hai-Tao Wang, Guo-Xin Wang et al.
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