Automated Multi-Agent Organization Design: From Architecture Search to Organizational Learning

Key points

• Agentic system design is increasingly shifting from hand-crafted prompts and workflows toward automated search over agentic programs and interaction structures, with multi-agent systems receiving growing attention.1
• Yet a central question remains unresolved: when does an automatically generated multi-agent structure exhibit a functionally meaningful division of responsibility?1
• We argue that automated multi-agent design should move beyond searching for effective architectures toward identifying which responsibilities are functionally necessary, how they should be allocated, and when they should change.1
• AMOD provides a principled foundation for evidence-based and adaptive multi-agent organization design.1

Sources (1)

• [1]Automated Multi-Agent Organization Design: From Architecture Search to Organizational Learning
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 20, 02:47 AM

  To explore this, we propose Automated Multi-Agent Organization Design (AMOD), which treats organization itself as a first-class design object, explicitly modeling how agent teams are composed, what functional responsibilities the agents assume, how they coordinate, and how collective decisions are made.

  Agentic system design is increasingly shifting from hand-crafted prompts and workflows toward automated search over agentic programs and interaction structures, with multi-agent systems receiving growing attention.

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