VirtLab: An AI-Powered System for Flexible, Customizable, and Large-scale Team Simulations

TL;DR

VirtLab is a versatile, scalable simulation platform using AI agents to model team collaboration in complex environments, supporting both technical and non-technical users for hypothesis testing.

Contribution

It introduces VirtLab, a customizable multi-agent simulation system that overcomes existing limitations by supporting flexible, spatial, and large-scale team simulations with an accessible interface.

Findings

Effective comparison of ground truth and simulated data

Supports diverse simulation scenarios and user types

Enhances understanding of team behaviors in complex settings

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.