Assemble Your Crew: Automatic Multi-agent Communication Topology Design via Autoregressive Graph Generation

Understand

Multi-agent systems (MAS) based on large language models (LLMs) have emerged as a powerful solution for dealing with complex problems across diverse domains.

• The effectiveness of MAS is critically dependent on its collaboration topology, which has become a focal point for automated design research.
• However, existing approaches are fundamentally constrained by their reliance on a template graph modification paradigm with a predefined set of agents and hard-coded interaction structures, significantly limiting their adaptability to task-specific requirements.
• To address these limitations, we reframe MAS design as a conditional autoregressive graph generation task, where both the system composition and structure are designed jointly.