mlsanityData to 14 Oct 2026

Multiagent Cooperation and Competition with Deep Reinforcement Learning

arXiv 1511.08779 ↗First posted 27 Nov 2015cs.AI cs.LG q-bio.NCcited by 184

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Cited by 21 in Deep reinforcement learning methods, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Multiagent systems appear in most social, economical, and political situations. In the present work we extend the Deep Q-Learning Network architecture proposed by Google DeepMind to multiagent environments and investigate how two agents controlled by independent Deep Q-Networks interact in the classic videogame Pong. By manipulating the classical rewarding scheme of Pong we demonstrate how competitive and collaborative behaviors emerge. Competitive agents learn to play and score efficiently. Agents trained under collaborative rewarding schemes find an optimal strategy to keep the ball in the game as long as possible. We also describe the progression from competitive to collaborative behavior. The present work demonstrates that Deep Q-Networks can become a practical tool for studying the decentralized learning of multiagent systems living in highly complex environments.

Key facts. Cited by 184 papers in the map (data through 14 Oct 2026). First posted on arXiv 27 Nov 2015.

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Citing papers per year: 2021: 43; 2022: 34; 2023: 28; 2024: 38; 2025: 23; 2026: 18.

184 papers.

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  1. 2022A Survey of Multi-Agent Deep Reinforcement Learning with Communicationcited by 104
  2. 2021Federated Reinforcement Learning: Techniques, Applications, and Open Challengescited by 81
  3. 2023JaxMARL: Multi-Agent RL Environments and Algorithms in JAXcited by 63
  4. 2021Cooperative Exploration for Multi-Agent Deep Reinforcement Learningcited by 57
  5. 2024An Introduction to Centralized Training for Decentralized Execution in Cooperative Multi-Agent Reinforcement Learningcited by 50
  6. 2022Towards a Standardised Performance Evaluation Protocol for Cooperative MARLcited by 49
  7. 2022Sound Adversarial Audio-Visual Navigationcited by 48
  8. 2021Deep Multiagent Reinforcement Learning: Challenges and Directionscited by 42
  9. 2023Leveraging Factored Action Spaces for Efficient Offline Reinforcement Learning in Healthcarecited by 42
  10. 2022Multi-agent Dynamic Algorithm Configurationcited by 36
  11. 2022Scalable Multi-Agent Reinforcement Learning through Intelligent Information Aggregationcited by 36
  12. 2023Multi-agent Reinforcement Learning: A Comprehensive Surveycited by 33
38 more
  1. 2021Distributed Heuristic Multi-Agent Path Finding with Communicationcited by 32
  2. 2024LLaMAR: Long-Horizon Planning for Multi-Agent Robots in Partially Observable Environmentscited by 32
  3. 2021RMIX: Learning Risk-Sensitive Policies for Cooperative Reinforcement Learning Agentscited by 31
  4. 2021Towards Distraction-Robust Active Visual Trackingcited by 30
  5. 2021Deep Reinforcement Learning Versus Evolution Strategies: A Comparative Surveycited by 28
  6. 2022Quantum Multi-Agent Meta Reinforcement Learningcited by 23
  7. 2021A Cooperative-Competitive Multi-Agent Framework for Auto-bidding in Online Advertisingcited by 22
  8. 2022Towards Comprehensive Testing on the Robustness of Cooperative Multi-agent Reinforcement Learningcited by 21
  9. 2021Intelligent Electric Vehicle Charging Recommendation Based on Multi-Agent Reinforcement Learningcited by 20
  10. 2023MAC-PO: Multi-Agent Experience Replay via Collective Priority Optimizationcited by 20
  11. 2021Co-GAIL: Learning Diverse Strategies for Human-Robot Collaborationcited by 17
  12. 2023Attacking Cooperative Multi-Agent Reinforcement Learning by Adversarial Minority Influencecited by 17
  13. 2024KoMA: Knowledge-driven Multi-agent Framework for Autonomous Driving with Large Language Modelscited by 17
  14. 2021Value Function is All You Need: A Unified Learning Framework for Ride Hailing Platformscited by 16
  15. 2021Coordinated Proximal Policy Optimizationcited by 16
  16. 2022Distributed Reinforcement Learning for Robot Teams: A Reviewcited by 16
  17. 2022LDSA: Learning Dynamic Subtask Assignment in Cooperative Multi-Agent Reinforcement Learningcited by 15
  18. 2022Statistical Deep Learning for Spatial and Spatio-Temporal Datacited by 15
  19. 2023Improving Generalization and Data Efficiency with Diffusion in Offline Multi-agent RLcited by 15
  20. 2021Attention-based Reinforcement Learning for Real-Time UAV Semantic Communicationcited by 14
  21. 2025Advancing Audio-Visual Navigation Through Multi-Agent Collaboration in 3D Environmentscited by 14
  22. 2021HAMMER: Multi-Level Coordination of Reinforcement Learning Agents via Learned Messagingcited by 13
  23. 2023Dealing With Non-stationarity in Decentralized Cooperative Multi-Agent Deep Reinforcement Learning via Multi-Timescale Learningcited by 13
  24. 2021Centralized Model and Exploration Policy for Multi-Agent RLcited by 12
  25. 2022Value Functions Factorization with Latent State Information Sharing in Decentralized Multi-Agent Policy Gradientscited by 12
  26. 2023Effective and Stable Role-Based Multi-Agent Collaboration by Structural Information Principlescited by 12
  27. 2021Spatial Intention Maps for Multi-Agent Mobile Manipulationcited by 11
  28. 2022MIXRTs: Toward Interpretable Multi-Agent Reinforcement Learning via Mixing Recurrent Soft Decision Treescited by 11
  29. 2024Conservative and Risk-Aware Offline Multi-Agent Reinforcement Learningcited by 10
  30. 2024Sable: a Performant, Efficient and Scalable Sequence Model for MARLcited by 10
  31. 2022Agent-Temporal Attention for Reward Redistribution in Episodic Multi-Agent Reinforcement Learningcited by 9
  32. 2023Adaptive action supervision in reinforcement learning from real-world multi-agent demonstrationscited by 9
  33. 2024Beyond the Edge: An Advanced Exploration of Reinforcement Learning for Mobile Edge Computing, its Applications, and Future Research Trajectoriescited by 9
  34. 2024Dispelling the Mirage of Progress in Offline MARL through Standardised Baselines and Evaluationcited by 9
  35. 2021Local Patch AutoAugment with Multi-Agent Collaborationcited by 8
  36. 2021Emergence of Theory of Mind Collaboration in Multiagent Systemscited by 8
  37. 2021Renewable energy integration and microgrid energy trading using multi-agent deep reinforcement learningcited by 8
  38. 2023Optimization of Image Transmission in a Cooperative Semantic Communication Networkscited by 8

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