mlsanityData to 7 Oct 2026

Prompt Sensitivity of Generative Agents: Evidence from an Epidemic Model

arXiv 2608.26221 ↗First posted 26 Aug 2026physics.soc-ph cs.AI cs.LGcited by 0

On the map: LLM agents and tool use → Social simulation and multi-agent debate

Abstract (arXiv)

As generative AI gains traction, researchers are investigating its potential to serve as proxies for humans. From undergoing cognitive psychology experiments to experiencing an epidemic, generative agents, agents powered by generative AI models, produce realistic human behavior when prompted. This study explores the sensitivity of these generative agents' behavior to prompt modifications and varied persona names of the agents. To assess this sensitivity, we use a generative agent epidemic model, wherein each agent is prompted daily on whether it wants to isolate or commingle with other agents. We found that using synonymous prompts results in negligible changes to the model's outcomes. However, minor variations in prompts, as well as contextual changes, do influence the model's results. Lastly, our data indicates that different persona names assigned to generative agents, specifically those imbued with personas, do not significantly impact epidemic outcomes.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Social simulation and multi-agent debate, one of 16 directions in LLM agents and tool use. Builds on 14 of its 24 references that are in the map. First posted on arXiv 26 Aug 2026.

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14 of 24 references.

Closest ancestors · 3

Same direction, newest first

  1. 2023Generative Agent-Based Modeling: Unveiling Social System Dynamics through Coupling Mechanistic Models with Generative Artificial Intelligence20 Sep
  2. 2023Epidemic Modeling with Generative Agents11 Jul
  3. 2023Blind Judgement: Agent-Based Supreme Court Modelling With GPT12 Jan

Other references · 11

  1. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  2. 2023A Survey on Large Language Model based Autonomous Agentscited by 2,203
  3. 2022Inner Monologue: Embodied Reasoning through Planning with Language Modelscited by 1,057
  4. 2022Out of One, Many: Using Language Models to Simulate Human Samplescited by 737
  5. 2022Using cognitive psychology to understand GPT-3cited by 389
  6. 2022Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLPcited by 316
  7. 2022Social Simulacra: Creating Populated Prototypes for Social Computing Systemscited by 300
  8. 2021AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Promptscited by 265
  9. 2023S3: Social-network Simulation System with Large Language Model-Empowered Agentscited by 228
  10. 2023Playing repeated games with Large Language Modelscited by 213
  11. 2022On the Robustness of Dialogue History Representation in Conversational Question Answering: A Comprehensive Study and a New Prompt-based Methodcited by 12

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