mlsanityData to 14 Oct 2026

Multi-Agent Reinforcement Learning for Resources Allocation Optimization: A Survey

arXiv 2504.21048 ↗First posted 29 Apr 2025cs.MA cs.AI cs.LGcited by 14

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Abstract (arXiv)

Multi-Agent Reinforcement Learning (MARL) has become a powerful framework for numerous real-world applications, modeling distributed decision-making and learning from interactions with complex environments. Resource Allocation Optimization (RAO) benefits significantly from MARL's ability to tackle dynamic and decentralized contexts. MARL-based approaches are increasingly applied to RAO challenges across sectors playing pivotal roles to Industry 4.0 developments. This survey provides a comprehensive review of recent MARL algorithms for RAO, encompassing core concepts, classifications, and a structured taxonomy. By outlining the current research landscape and identifying primary challenges and future directions, this survey aims to support researchers and practitioners in leveraging MARL's potential to advance resource allocation solutions.

Key facts. Cited by 14 papers in the map (data through 14 Oct 2026). Builds on 44 of its 181 references that are in the map. First posted on arXiv 29 Apr 2025.

Builds on

44 of 181 references.

References · 44

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32 more
  1. 2021Distributed Learning in Wireless Networks: Recent Progress and Future Challengescited by 129
  2. 2018Deep Reinforcement Learning for Multi-Agent Systems: A Review of Challenges, Solutions and Applicationscited by 127
  3. 2019CityFlow: A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenariocited by 115
  4. 2022A Survey of Multi-Agent Deep Reinforcement Learning with Communicationcited by 104
  5. 2018Multi-Agent Deep Reinforcement Learning for Dynamic Power Allocation in Wireless Networkscited by 70
  6. 2020Single and Multi-Agent Deep Reinforcement Learning for AI-Enabled Wireless Networks: A Tutorialcited by 60
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  8. 2018Multi-Agent Reinforcement Learning Based Resource Allocation for UAV Networkscited by 56
  9. 2021Multi-Agent Reinforcement Learning for Active Voltage Control on Power Distribution Networkscited by 54
  10. 2019Efficient Communication in Multi-Agent Reinforcement Learning via Variance Based Controlcited by 46
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  12. 2021Deep Multiagent Reinforcement Learning: Challenges and Directionscited by 42
  13. 2021Deep Multi-agent Reinforcement Learning for Highway On-Ramp Merging in Mixed Trafficcited by 41
  14. 2021UPDeT: Universal Multi-agent Reinforcement Learning via Policy Decoupling with Transformerscited by 39
  15. 2020A Review of Deep Reinforcement Learning for Smart Building Energy Managementcited by 38
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  20. 2021AoI-Aware Resource Allocation for Platoon-Based C-V2X Networks via Multi-Agent Multi-Task Reinforcement Learningcited by 18
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  27. 2023ContainerGym: A Real-World Reinforcement Learning Benchmark for Resource Allocationcited by 6
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 5; 2026: 9.

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  1. 2025OM2P: Offline Multi-Agent Mean-Flow Policycited by 8
  2. 2025LEED: A Highly Efficient and Scalable LLM-Empowered Expert Demonstrations Framework for Multi-Agent Reinforcement Learningcited by 6
  3. 2025Adaptive GPU Resource Allocation for Multi-Agent Collaborative Reasoning in Serverless Environmentscited by 4
  4. 2026Can LLM Agents Be CFOs? Benchmarking Long-Horizon Resource Allocation in an Uncertain Enterprise Environmentcited by 4
  5. 2025Robust and Efficient Communication in Multi-Agent Reinforcement Learningcited by 2
  6. 2026Bridging MARL to SARL: An Order-Independent Multi-Agent Transformer via Latent Consensuscited by 2
  7. 2026FedCritic: Serverless Federated Critic Learning-based Resource Allocation for Multi-Cell OFDMA in 6Gcited by 1
  8. 2026Scalable Constrained Multi-Agent Reinforcement Learning via State Augmentation and Consensus for Separable Dynamicscited by 1
  9. 2025MaRCA: Multi-Agent Reinforcement Learning for Dynamic Computation Allocation in Large-Scale Recommender Systemscited by 0
  10. 2026Harnessing Implicit Cooperation: A Multi-Agent Reinforcement Learning Approach Towards Decentralized Local Energy Marketscited by 0
  11. 2026Characterizing MARL for Energy Control: A Multi-KPI Benchmark on the CityLearn Environmentcited by 0
  12. 2026HADT: A Heterogeneous Multi-Agent Differential Transformer for Autonomous Earth Observation Satellite Clustercited by 0
2 more
  1. 2026A Self-Calibrating Agentic AI Framework for Autonomous Edge Resource Allocationcited by 0
  2. 2026Multi-Agent Reinforcement Learning via Agent-Specific Preferencecited by 0

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  3. 2025Optimization without Future Compromises? Decentralized Coordination via Collective and Reinforcement Learning
  4. 2024Game Theory and Multi-Agent Reinforcement Learning : From Nash Equilibria to Evolutionary Dynamics
  5. 2024MARL-LNS: Cooperative Multi-agent Reinforcement Learning via Large Neighborhoods Search
  6. 2025The Heterogeneous Multi-Agent Challenge
  7. 2025Multi-Agent Reinforcement Learning in Intelligent Transportation Systems: A Comprehensive Survey
  8. 2026Multi-Agent Reinforcement Learning for V2X Resource Allocation: Disentangling MARL Challenges Through Benchmarking