Research map / Multi-agent systems and games / Cooperative multi-agent RL
Learning the Value of Teamwork to Form Efficient Teams
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| value pairs of players and add interactional alignment instead of singleton player values | teamwork MIP · 2018 World Cup outcome prediction | accuracy (%): 50 -> 60.2 | Helped |
| use pair values instead of individual metrics | teamwork MIP · Passes prediction | RMSE: 105.69 -> 57.07 | Helped |
| use pair values instead of individual metrics | teamwork MIP · Shots prediction | RMSE: 4.33 -> 3.74 | Helped |
| use pair values instead of individual metrics | teamwork MIP · Goals Against prediction | RMSE: 1.14 -> 1.06 | Helped |
| use pair-based team formation instead of singleton formation for matching human manager | teamwork MIP · team selection vs human manager | average difference: 2.3 per game | Helped |
| use walk frequency instead of centrality for singleton values (ablation) | MIP · 2018 World Cup outcome prediction | accuracy (%): 50 -> 46.1 | Hurt |
| use distance from event instead of centrality for singleton values (ablation) | MIP · 2018 World Cup outcome prediction | accuracy (%): 50 -> 51.6 | No clear effect |
Closest papers by meaning
- Optimising Spatial Teamwork Under Uncertainty (AAAI 2025 · similarity 0.86)
- Ad Hoc Teamwork via Offline Goal-Based Decision Transformers (ICML 2025 · similarity 0.84)
- Open Ad Hoc Teamwork with Cooperative Game Theory (ICML 2024 · similarity 0.84)
- Team-Fictitious Play for Reaching Team-Nash Equilibrium in Multi-team Games (NeurIPS 2024 · similarity 0.84)
- ROTATE: Regret-driven Open-ended Training for Ad Hoc Teamwork (NeurIPS 2026 · similarity 0.83)
- Probabilistic Modeling of Interpersonal Coordination Processes (ICML 2024 · similarity 0.83)
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