A consensus-based distributed algorithm for constrained MARL with separable dynamics achieves linear scalability and bounded constraint violations through state-augmented policies and dual variable agreement.
Guannan Qu, Yiheng Lin, Adam Wierman, and Na Li
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Scalable Constrained Multi-Agent Reinforcement Learning via State Augmentation and Consensus for Separable Dynamics
A consensus-based distributed algorithm for constrained MARL with separable dynamics achieves linear scalability and bounded constraint violations through state-augmented policies and dual variable agreement.