English

Simulating Teams with LLM Agents: Interactive 2D Environments for Studying Human-AI Dynamics

Human-Computer Interaction 2025-10-10 v1

Abstract

Enabling users to create their own simulations offers a powerful way to study team dynamics and performance. We introduce VirTLab, a system that allows researchers and practitioners to design interactive, customizable simulations of team dynamics with LLM-based agents situated in 2D spatial environments. Unlike prior frameworks that restrict scenarios to predefined or static tasks, our approach enables users to build scenarios, assign roles, and observe how agents coordinate, move, and adapt over time. By bridging team cognition behaviors with scalable agent-based modeling, our system provides a testbed for investigating how environments influence coordination, collaboration, and emergent team behaviors. We demonstrate its utility by aligning simulated outcomes with empirical evaluations and a user study, underscoring the importance of customizable environments for advancing research on multi-agent simulations. This work contributes to making simulations accessible to both technical and non-technical users, supporting the design, execution, and analysis of complex multi-agent experiments.

Keywords

Cite

@article{arxiv.2510.08242,
  title  = {Simulating Teams with LLM Agents: Interactive 2D Environments for Studying Human-AI Dynamics},
  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:2510.08242},
  year   = {2025}
}

Comments

29 pages

R2 v1 2026-07-01T06:26:50.921Z