Research map / Multi-agent systems and games / Cooperative multi-agent RL
Coordination Between Individual Agents in Multi-Agent Reinforcement Learning
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use Pearson correlation instead of Spearman correlation (ablation) | ALC-MADDPG · Physical deception, Covert communication, Keep-away, Complex predator-prey | mean episode reward | Helped |
| Use Pearson correlation instead of Kendall correlation (ablation) | ALC-MADDPG · Physical deception, Covert communication, Keep-away, Complex predator-prey | mean episode reward | Helped |
| Set correlation threshold G to 0.3 instead of 0.4, 0.5, 0.6, or 0.7 (ablation) | ALC-MADDPG · Physical deception | mean episode reward | Helped |
| Set correlation threshold G to 0.3 instead of 0.4, 0.5, 0.6, or 0.7 (ablation) | ALC-MADDPG · Complex predator-prey | mean episode reward | Helped |
| Vary correlation threshold G among 0.3, 0.4, 0.5, 0.6, and 0.7 (ablation) | ALC-MADDPG · Covert communication and Keep-away | mean episode reward | No clear effect |
| Use a lower correlation threshold G (ablation) | ALC-MADDPG · Physical deception and Complex predator-prey | mean episode reward | Mixed |
| Use agent-level correlation to select communication and shape rewards | MADDPG · Physical deception | mean episode reward | Helped |
| Use agent-level correlation to select communication and shape rewards | MADDPG · Covert communication | mean episode reward | Helped |
| Use agent-level correlation to select communication and shape rewards | MADDPG · Keep-away | mean episode reward | Helped |
| Use agent-level correlation to select communication and shape rewards | MADDPG · Complex predator-prey | mean episode reward | Helped |
Closest papers by meaning
- Revisiting Some Common Practices in Cooperative Multi-Agent Reinforcement Learning (ICML 2022 · similarity 0.91)
- Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms in Cooperative Tasks (NeurIPS 2021 · similarity 0.90)
- Situation-Dependent Causal Influence-Based Cooperative Multi-Agent Reinforcement Learning (AAAI 2024 · similarity 0.89)
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- Decomposing Temporal Equilibrium Strategy for Coordinated Distributed Multi-Agent Reinforcement Learning (AAAI 2024 · similarity 0.89)
- A Principle of Targeted Intervention for Multi-Agent Reinforcement Learning (NeurIPS 2025 · similarity 0.88)
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