Topological Structure Learning Should Be A Research Priority for LLM-Based Multi-Agent Systems

Understand

Large Language Model-based Multi-Agent Systems (MASs) have emerged as a powerful paradigm for tackling complex tasks through collaborative intelligence.

• However, the topology of these systems--how agents in MASs should be configured, connected, and coordinated--remains largely unexplored.
• In this position paper, we call for a paradigm shift toward \emph{topology-aware MASs} that explicitly model and dynamically optimize the structure of inter-agent interactions.
• We identify three fundamental components--agents, communication links, and overall topology--that collectively determine the system's adaptability, efficiency, robustness, and fairness.