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Hybrid Offline-Online Multi-Agent Decision Transformers for Wireless Resource Management
This paper develops a hybrid offline-online multi-agent reinforcement learning framework based on decision transformers. The policy is first pretrained offline via supervised sequence modeling of trajectories generated by existing policies, providing a safe and sample-efficient initialization. It is
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