Simulating how team members collaborate within complex environments using Agentic AI is a promising approach to explore hypotheses grounded in social science theories and study team behaviors. We introduce VirtLab, a user-friendly, customizable, multi-agent, and scalable team simulation system that enables testing teams with LLM-based agents in spatial and temporal settings. This system addresses the current frameworks' design and technical limitations that do not consider flexible simulation scenarios and spatial settings. VirtLab contains a simulation engine and a web interface that enables both technical and non-technical users to formulate, run, and analyze team simulations without programming. We demonstrate the system's utility by comparing ground truth data with simulated scenarios.
@article{arxiv.2508.04634,
title = {VirtLab: An AI-Powered System for Flexible, Customizable, and Large-scale Team Simulations},
author = {Mohammed Almutairi and Charles Chiang and Haoze Guo and Matthew Belcher and Nandini Banerjee and Maria Milkowski and Svitlana Volkova and Daniel Nguyen and Tim Weninger and Michael Yankoski and Trenton W. Ford and Diego Gomez-Zara},
journal= {arXiv preprint arXiv:2508.04634},
year = {2025}
}