Agents that Matter: How Subtle Choices Shape Agent Attribution in Multi-Agent Systems
As multi-agent systems (MAS) become increasingly complex, identifying the contributions of agents is critical for system optimization. However, existing approaches lack a unified formulation for credit assignment. In this work, we formalize agent attribution as a cooperative game, parameterized by the coalition distribution, intervention protocol, and target metric. Using this framework, we demonstrate that intervention protocols induce distinct games: Agent ablation isolates structural bottlenecks, whereas introspective LLM judges fail to faithfully approximate this behavior. We further find that Leave-One-Out (LOO) identifies bottleneck agents as effectively as combinatorial methods at ...
| Authors | Mingyu Lu, Yushan Huang, Chris Lin et al. |
|---|---|
| Primary category | cs.MA |
| Published | 26 May 2026 |
| Last updated at source | 26 September 2026 |
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