1 citations · 1 across the 4 of their papers we have counts for
4 papers
Simulating Teams with LLM Agents: Interactive 2D Environments for Studying Human-AI Dynamics
Mohammed Almutairi, Charles Chiang, Haoze Guo +9
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 practitioner…
VirtLab: An AI-Powered System for Flexible, Customizable, and Large-scale Team Simulations
Mohammed Almutairi, Charles Chiang, Haoze Guo +9
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 tea…
Exploring Big Five Personality and AI Capability Effects in LLM-Simulated Negotiation Dialogues
Myke C. Cohen, Zhe Su, Hsien-Te Kao +4
This paper presents an evaluation framework for agentic AI systems in mission-critical negotiation contexts, addressing the need for AI agents that can adapt to diverse human opera…
Exploratory Models of Human-AI Teams: Leveraging Human Digital Twins to Investigate Trust Development
Daniel Nguyen, Myke C. Cohen, Hsien-Te Kao +4
As human-agent teaming (HAT) research continues to grow, computational methods for modeling HAT behaviors and measuring HAT effectiveness also continue to develop. One rising metho…