mlsanityData to 7 Oct 2026

Survey of Recent Multi-Agent Reinforcement Learning Algorithms Utilizing Centralized Training

arXiv 2107.14316 ↗First posted 29 Jul 2021cs.MA cs.AI cs.LGcited by 16

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Abstract (arXiv)

Much work has been dedicated to the exploration of Multi-Agent Reinforcement Learning (MARL) paradigms implementing a centralized learning with decentralized execution (CLDE) approach to achieve human-like collaboration in cooperative tasks. Here, we discuss variations of centralized training and describe a recent survey of algorithmic approaches. The goal is to explore how different implementations of information sharing mechanism in centralized learning may give rise to distinct group coordinated behaviors in multi-agent systems performing cooperative tasks.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). Builds on 25 of its 47 references that are in the map. First posted on arXiv 29 Jul 2021.

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25 of 47 references.

References · 25

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13 more
  1. 2017Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learningcited by 114
  2. 2019Dealing with Non-Stationarity in Multi-Agent Deep Reinforcement Learningcited by 90
  3. 2018Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Spacecited by 54
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  5. 2020Forethought and Hindsight in Credit Assignmentcited by 16
  6. 2019Deep Multi-Agent Reinforcement Learning with Discrete-Continuous Hybrid Action Spacescited by 15
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  13. 2021Heterogeneous Noisy Short Signal Camouflage in Multi-Domain Environment Decision-Makingcited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 4; 2023: 5; 2024: 2; 2025: 1; 2026: 2.

16 papers.

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  1. 2021Causal Multi-Agent Reinforcement Learning: Review and Open Problemscited by 16
  2. 2023Transformers in Reinforcement Learning: A Surveycited by 11
  3. 2021LINDA: Multi-Agent Local Information Decomposition for Awareness of Teammatescited by 9
  4. 2025HCRide: Harmonizing Passenger Fairness and Driver Preference for Human-Centered Ride-Hailingcited by 7
  5. 2024A Taxonomy of Architecture Options for Foundation Model-based Agents: Analysis and Decision Modelcited by 4
  6. 2022Bilateral Deep Reinforcement Learning Approach for Better-than-human Car Following Modelcited by 3
  7. 2022Renaissance Robot: Optimal Transport Policy Fusion for Learning Diverse Skillscited by 2
  8. 2026Socially-Weighted Alignment: A Game-Theoretic Framework for Multi-Agent LLM Systemscited by 2
  9. 2022Strategic Maneuver and Disruption with Reinforcement Learning Approaches for Multi-Agent Coordinationcited by 1
  10. 2023User-centric Heterogeneous-action Deep Reinforcement Learning for Virtual Reality in the Metaverse over Wireless Networkscited by 1
  11. 2023Orchestration of Emulator Assisted Mobile Edge Tuning for AI Foundation Models: A Multi-Agent Deep Reinforcement Learning Approachcited by 1
  12. 2023Privacy-Engineered Value Decomposition Networks for Cooperative Multi-Agent Reinforcement Learningcited by 1
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  1. 2022Emergent Behaviors in Multi-Agent Target Acquisitioncited by 0
  2. 2023Virtual Reality in Metaverse over Wireless Networks with User-centered Deep Reinforcement Learningcited by 0
  3. 2024Cooperative Path Planning with Asynchronous Multiagent Reinforcement Learningcited by 0
  4. 2026GPEvac: GNN-Based PPO for Adaptive Evacuation Routing During Shooting Eventscited by 0