Scaling Behavior of Single LLM-Driven Multi-Agent Systems
The burgeoning field of LLM-based Multi-Agent Systems (MAS) promises to tackle complex tasks through collaborative intelligence, yet fundamental questions regarding their scaling behavior and intrinsic collective dynamics remain underexplored. This paper systematically investigates how the performance of a homogeneous MAS evolves as the number of agents increases, isolating the variable of collaboration from model or knowledge heterogeneity. We propose the Sequential Iterative Multi-Agent System
Record details
Published: 30 May 2026
Source: arXiv
Category: Research
Topics: Agents & autonomy · Finance, VC & PE
Retrieved: 14 July 2026
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ethics.ai (30 May 2026), “Scaling Behavior of Single LLM-Driven Multi-Agent Systems,” evidence record 3393, https://ethics.ai/record/3393 (originally published by arXiv).
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