Toward an Organizational Science of Multi-Agent LLM Systems: Decoupling Who, How, and Which Algorithm
Multi-agent frameworks built on large language models (LLMs) routinely entangle three logically distinct concerns: who is on the team (organization), how members align (coordination), and which algorithm fuses their work (collaboration protocol). IMACS (Intelligent Multi-Agent Collaboration System) separates the three into orthogonal, independently swappable layers. Classic organizational theory (Belbin roles, Mintzberg coordination, RACI accountability) becomes executable, validated configuration, and the framework places six published collaboration algorithms behind a common interface while exposing roles, coordination, and accountability as independently configurable factors. We use th...
| Authors | Huan Chen, Xiang Song, Jian Jin et al. |
|---|---|
| Primary category | cs.AI |
| Published | 28 July 2026 |
| Last updated at source | 28 July 2026 |
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