# Control Charts for Multi-agent Systems

arXiv: https://arxiv.org/abs/2605.11135 · HTML: https://mlsanity.com/paper/2605.11135/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use.
- Builds on 18 of its 29 references that are in the map.
- First posted on arXiv 11 May 2026.

## Placed in

- LLM agents and tool use / [Agent threats, guardrails and governance](https://mlsanity.com/agents/agent-threats-guardrails-and-governance/)

## Builds on (most cited first, 18 of 18)

- [GPT-4o System Card](https://mlsanity.com/paper/2410.21276/) (2024)
- [Generative Agents: Interactive Simulacra of Human Behavior](https://mlsanity.com/paper/2304.03442/) (2023)
- [Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training](https://mlsanity.com/paper/2401.05566/) (2024)
- [The Platonic Representation Hypothesis](https://mlsanity.com/paper/2405.07987/) (2024)
- [Nomic Embed: Training a Reproducible Long Context Text Embedder](https://mlsanity.com/paper/2402.01613/) (2024)
- [Simulating Opinion Dynamics with Networks of LLM-based Agents](https://mlsanity.com/paper/2311.09618/) (2023)
- [Evaluating Language-Model Agents on Realistic Autonomous Tasks](https://mlsanity.com/paper/2312.11671/) (2023)
- [Learning on LoRAs: GL-Equivariant Processing of Low-Rank Weight Spaces for Large Finetuned Models](https://mlsanity.com/paper/2410.04207/) (2024)
- [Comparing Foundation Models using Data Kernels](https://mlsanity.com/paper/2305.05126/) (2023)
- [Tracking the perspectives of interacting language models](https://mlsanity.com/paper/2406.11938/) (2024)
- [Consistent estimation of generative model representations in the data kernel perspective space](https://mlsanity.com/paper/2409.17308/) (2024)
- [Statistical inference on black-box generative models in the data kernel perspective space](https://mlsanity.com/paper/2410.01106/) (2024)
- [Multiple Network Embedding for Anomaly Detection in Time Series of Graphs](https://mlsanity.com/paper/2008.10055/) (2020)
- [Euclidean mirrors and dynamics in network time series](https://mlsanity.com/paper/2205.06877/) (2022)
- [Investigating social alignment via mirroring in a system of interacting language models](https://mlsanity.com/paper/2412.06834/) (2024)
- [Euclidean mirrors and first-order changepoints in network time series](https://mlsanity.com/paper/2405.11111/) (2024)
- [Detecting Perspective Shifts in Multi-agent Systems](https://mlsanity.com/paper/2512.05013/) (2025)
- [Gaussian mixture models as a proxy for interacting language models](https://mlsanity.com/paper/2506.00077/) (2025)

## Built on by (most cited first, 1 of 1)

- [Sequential statistical inference for Large Language Models: Representation, validity, and monitoring](https://mlsanity.com/paper/2606.07624/) (2026)

## Abstract (arXiv)

Generative agents have proven to be powerful assistants in a wide variety of contexts. Given this success, users are now deploying agents with minimal restrictions in open ended, multi-agent environments. Current methods for monitoring the dynamics of open-ended multi-agent systems are limited to qualitative inspection. In this paper, we extend the process-theoretic notion of adaptive control charts to multi-agent systems to enable automated monitoring. Using simulation, we demonstrate that adaptive control charts are necessary for monitoring multi-agent systems that can learn from their environment. We further demonstrate, both empirically and theoretically, that adaptive control charts are susceptible to adversarial agents that defect sufficiently slowly. These results illustrate a fundamental tradeoff in multi-agent system control: either agents in a system cannot learn or the system is susceptible to adversaries.