mlsanityData to 14 Oct 2026

Hybrid Offline-Online Multi-Agent Decision Transformers for Wireless Resource Management

arXiv 2608.28878 ↗First posted 28 Aug 2026eess.SY cs.AI cs.SYcited by 0

On the map: Offline RL and imitation learning from data → Offline multi-agent RL

Abstract (arXiv)

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 then fine-tuned online using a hybrid objective that incorporates critic-guided gradients, enabling performance improvements beyond the offline policy. To facilitate stable offline-to-online transfer and effective multi-agent coordination, the framework incorporates return-weighted sampling, a critic conditioned on neighbors' actions, and neighborhood-correlated exploration. The approach is fully distributed: both training and execution rely only on local observations and limited information exchange among neighboring agents. Evaluations with dynamic traffic arrivals in two settings: (i) joint scheduling and power allocation and (ii) coordinated beamforming, show that the proposed method achieves quality-of-service (QoS) performance comparable to centralized methods. Moreover, when pretrained on lower-quality datasets, online fine-tuning is also observed to surpass the initial offline policy. These results demonstrate a promising learning-based alternative for wireless resource management.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Offline multi-agent RL, one of 13 directions in Offline RL and imitation learning from data. Builds on 15 of its 29 references that are in the map. First posted on arXiv 28 Aug 2026.

Builds on

15 of 29 references.

Closest ancestors · 3

Same direction, newest first

  1. 2025An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management22 Jan
  2. 2023Advancing RAN Slicing with Offline Reinforcement Learning16 Dec
  3. 2023Offline Reinforcement Learning for Wireless Network Optimization with Mixture Datasets19 Nov

Other references · 12

  1. 2017Attention Is All You Needcited by 60,361
  2. 2018Addressing Function Approximation Error in Actor-Critic Methodscited by 2,417
  3. 2021Decision Transformer: Reinforcement Learning via Sequence Modelingcited by 1,546
  4. 2023Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuningcited by 237
  5. 2018Multi-Agent Deep Reinforcement Learning for Dynamic Power Allocation in Wireless Networkscited by 70
  6. 2024Q-value Regularized Transformer for Offline Reinforcement Learningcited by 29
  7. 2019Scalable Reinforcement Learning for Multi-Agent Networked Systemscited by 24
  8. 2024Decision Transformers for Wireless Communications: A New Paradigm of Resource Managementcited by 15
  9. 2024Reinforcement Learning Gradients as Vitamin for Online Finetuning Decision Transformerscited by 8
  10. 2020Deep Actor-Critic Learning for Distributed Power Control in Wireless Mobile Networkscited by 7
  11. 2023Multi-Agent Reinforcement Learning for Multi-Cell Spectrum and Power Allocationcited by 5
  12. 2023Deep Reinforcement Learning for Distributed Dynamic Coordinated Beamforming in Massive MIMO Cellular Networkscited by 3

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Not cited yet.

Similar, not cited

Close in wording, no citation either way

  1. 2026Selecting Offline Reinforcement Learning Algorithms for Stochastic Network Control
  2. 2025Multi-Agent Reinforcement Learning for Task Offloading in Wireless Edge Networks
  3. 2026Offline Multi-Agent Reinforcement Learning for 6G Communications: Fundamentals, Applications and Future Directions
  4. 2024Offline and Distributional Reinforcement Learning for Radio Resource Management
  5. 2021Offline Pre-trained Multi-Agent Decision Transformer: One Big Sequence Model Tackles All SMAC Tasks
  6. 2025Toward Trustworthy Digital Twins in AI Agent-based Wireless Network Optimization: Challenges, Solutions, and Opportunities
  7. 2024Streetwise Agents: Empowering Offline RL Policies to Outsmart Exogenous Stochastic Disturbances in RTC
  8. 2025Offline and Distributional Reinforcement Learning for Wireless Communications