VIRT-LAB: An AI-Powered System for Flexible, Customizable, and Large-scale Team Simulations
Year: 2025
Type: conference-paper
Abstract: 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 VirT-Lab, 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.VirT-Lab 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.
Authors: Mohammed Almutairi, Charles Chiang, Haoze Guo, Matthew Belcher, Nandini Banerjee, Maria Milkowski, Svitlana Volkova, Daniel Nguyen, Tim Weninger, Michael G Yankoski, Trenton W Ford, Diego Gómez-Zará
Institutions: University of Notre Dame, Aptima (United States), William & Mary
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4414565458