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An Improved Multi-Agent Algorithm for Cooperative and Competitive Environments by Identifying and Encouraging Cooperation among Agents

arXiv 2508.14131 ↗First posted 19 Aug 2025cs.MA cs.AIcited by 0

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Abstract (arXiv)

We propose an improved algorithm by identifying and encouraging cooperative behavior in multi-agent environments. First, we analyze the shortcomings of existing algorithms in addressing multi-agent reinforcement learning problems. Then, based on the existing algorithm MADDPG, we introduce a new parameter to increase the reward that an agent can obtain when cooperative behavior among agents is identified. Finally, we compare our improved algorithm with MADDPG in environments from PettingZoo. The results show that the new algorithm helps agents achieve both higher team rewards and individual rewards.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 11 of its 17 references that are in the map. First posted on arXiv 19 Aug 2025.

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References · 11

  1. 2017Proximal Policy Optimization Algorithmscited by 15,215
  2. 2017Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environmentscited by 1,558
  3. 2018QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learningcited by 708
  4. 2016Learning to Communicate with Deep Multi-Agent Reinforcement Learningcited by 575
  5. 2021Independent Policy Gradient Methods for Competitive Reinforcement Learningcited by 101
  6. 2019Dealing with Non-Stationarity in Multi-Agent Deep Reinforcement Learningcited by 93
  7. 2021Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learningcited by 25
  8. 2018Imitation Learning with Concurrent Actions in 3D Gamescited by 18
  9. 2023Asynchronous Multi-Agent Reinforcement Learning for Efficient Real-Time Multi-Robot Cooperative Explorationcited by 18
  10. 2023Partially Observable Mean Field Multi-Agent Reinforcement Learning Based on Graph-Attentioncited by 7
  11. 2021Multi-Agent Deep Deterministic Policy Gradient Algorithm for Peer-to-Peer Energy Trading Considering Distribution Network Constraintscited by 3

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  5. 2024The impact of behavioral diversity in multi-agent reinforcement learning
  6. 2024MESA: Cooperative Meta-Exploration in Multi-Agent Learning through Exploiting State-Action Space Structure
  7. 2025Learning Bilateral Team Formation in Cooperative Multi-Agent Reinforcement Learning
  8. 2025Constructive Conflict-Driven Multi-Agent Reinforcement Learning for Strategic Diversity