VirtLab: An AI-Powered System for Flexible, Customizable, and Large-scale Team Simulations
August 06, 2025 Β· Declared Dead Β· π Adjunct Proceedings of the 38th Annual ACM Symposium on User Interface Software and Technology
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Authors
Mohammed Almutairi, Charles Chiang, Haoze Guo, Matthew Belcher, Nandini Banerjee, Maria Milkowski, Svitlana Volkova, Daniel Nguyen, Tim Weninger, Michael Yankoski, Trenton W. Ford, Diego Gomez-Zara
arXiv ID
2508.04634
Category
cs.HC: Human-Computer Interaction
Citations
1
Venue
Adjunct Proceedings of the 38th Annual ACM Symposium on User Interface Software and Technology
Last Checked
4 months ago
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 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.
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