Research map / Multi-agent systems and games / Cooperative multi-agent RL
Iterated Reasoning with Mutual Information in Cooperative and Byzantine Decentralized Teaming
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use InfoPG instead of MOA | decentralized cooperative MARL · Co-op Pong | team reward: -0.3 -> 0.127 | Helped |
| Use Adv. InfoPG instead of MOA | decentralized cooperative MARL · Co-op Pong | team reward: -0.3 -> 0.25 | Helped |
| Use InfoPG instead of MOA | decentralized cooperative MARL · Pistonball | team reward: 4.10 -> 7.47 | Helped |
| Use Adv. InfoPG instead of MOA | decentralized cooperative MARL · Pistonball | team reward: 4.10 -> 7.33 | Helped |
| Use InfoPG instead of MOA | decentralized cooperative MARL · Multiwalker | team reward: 0.66 -> 3.56 | Helped |
| Use Adv. InfoPG instead of MOA | decentralized cooperative MARL · Multiwalker | team reward: 0.66 -> 11.81 | Helped |
| Use InfoPG instead of MOA | decentralized cooperative MARL · StarCraft II 3M | team reward: 2.78 -> 4.40 | Helped |
| Use Adv. InfoPG instead of MOA | decentralized cooperative MARL · StarCraft II 3M | team reward: 2.78 -> 3.73 | Helped |
| Increase reasoning depth from one step to k=2 or k=3 (ablation) | InfoPG · Co-op Pong | team reward | No clear effect |
| Increase reasoning depth from one step to k=2 or k=3 (ablation) | InfoPG · Pistonball and Multiwalker | team reward | Helped |
| Replace InfoPG with Adv. InfoPG when a random fraudulent agent is present (ablation) | Pistonball team · Pistonball fraudulent-agent experiment | team reward | Helped |
| Maximize MI without adapting to negative advantage in the presence of a random fraudulent agent (ablation) | InfoPG and MOA · Pistonball fraudulent-agent experiment | team reward | Hurt |
Closest papers by meaning
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- Mutual-Information Regularized Multi-Agent Policy Iteration (NeurIPS 2023 · similarity 0.89)
- Efficient Communication in Multi-Agent Reinforcement Learning with Implicit Consensus Generation (AAAI 2025 · similarity 0.88)
- Cautiously-Optimistic Knowledge Sharing for Cooperative Multi-Agent Reinforcement Learning (AAAI 2024 · similarity 0.88)
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