Research map / Multi-agent systems and games / Cooperative multi-agent RL
Learning Agent Communication under Limited Bandwidth by Message Pruning
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add adaptive message gating to ACML | ACML · Traffic control (simple, moderate, and complex) | reward: -37.6 -> -14.6; -103.5 -> -69.4; -2824.9 -> -2101.1 | Helped |
| Add adaptive message gating to ACML | ACML · Simple and moderate routing; simple and complex WAPC | reward: 0.317 -> 0.288; 0.263 -> 0.239; 0.665 -> 0.610; 0.480 -> 0.411 | Hurt |
| Add adaptive message gating to ACML | ACML · Traffic control, routing, and WAPC | message: 100.0% -> 23.9%; 100.0% -> 29.8%; 100.0% -> 25.8%; 100.0% -> 33.6%; 100.0% -> 27.9%; 100.0% -> 41.9%; 100.0% -> 37.7% | Helped |
| Add gating to CommNet | CommNet · Traffic control, routing, and WAPC | message: 100.0% -> 22.8%; 100.0% -> 34.3%; 100.0% -> 29.3%; 100.0% -> 35.2%; 100.0% -> 21.7%; 100.0% -> 19.8%; 100.0% -> 53.1%; 1 | Helped |
| Add gating to AMP | AMP · Traffic control, routing, and WAPC | message: 100.0% -> 18.6%; 100.0% -> 23.7%; 100.0% -> 19.1%; 100.0% -> 46.7%; 100.0% -> 35.0%; 100.0% -> 81.7%; 100.0% -> 57.2%; 1 | Helped |
| Replace the ACML message coordinator with mean aggregation (ablation) | ACML · Traffic control, routing, and WAPC | reward: -37.6 -> -32.9; -103.5 -> -96.1; -2824.9 -> -2661.5; 0.317 -> 0.321; 0.263 -> 0.267; 0.665 -> 0.673; 0.480 -> 0.493 | Helped |
| Replace the ACML message coordinator with attention aggregation (ablation) | ACML · Traffic control, routing, and WAPC | reward: -37.6 -> -24.5; -103.5 -> -91.8; -2824.9 -> -2359.7; 0.317 -> 0.329; 0.263 -> 0.271; 0.665 -> 0.689; 0.480 -> 0.506 | Helped |
| Use a fixed threshold targeting less than 30% message pruning (ablation) | Gated-ACML · Simple and moderate routing | reward: -8.46%; -7.03%; -13.59%; -12.14%; -4.88%; -3.25% | Helped |
| Use a fixed threshold targeting 70–90% message pruning (ablation) | Gated-ACML · Simple and moderate routing | reward: 9.27%; 10.06%; 14.01%; 13.25%; 18.60%; 19.50% | Hurt |
| Prune all messages using a fixed threshold (ablation) | Gated-ACML · Simple and moderate routing | reward: 59.35%; 65.42% | Hurt |
Closest papers by meaning
- Multi-Agent Reinforcement Learning with Communication-Constrained Priors (NeurIPS 2025 · similarity 0.87)
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- Efficient Communication in Multi-Agent Reinforcement Learning with Implicit Consensus Generation (AAAI 2025 · similarity 0.86)
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