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[2505.03795] Modeling Human Behavior in a Strategic Network Game with Complex Group Dynamics
Summary
This article explores modeling human behavior in strategic network games, focusing on the Junior High Game (JHG) and comparing various behavioral modeling methods to understand group dynamics.
Why It Matters
Understanding human behavior in networked environments is crucial for addressing societal issues like inequality and bullying. This research offers insights into effective modeling techniques that can enhance our grasp of complex social interactions, potentially informing interventions and policies.
Key Takeaways
- The hCAB model outperforms others by modeling the distribution of behavior rather than the mean.
- Community-aware behavior assumptions lead to more accurate simulations of human interactions.
- User studies indicate that hCAB agents are often indistinguishable from real humans, highlighting its effectiveness.
Computer Science > Social and Information Networks arXiv:2505.03795 (cs) [Submitted on 1 May 2025 (v1), last revised 18 Feb 2026 (this version, v3)] Title:Modeling Human Behavior in a Strategic Network Game with Complex Group Dynamics Authors:Jonathan Skaggs, Jacob W. Crandall View a PDF of the paper titled Modeling Human Behavior in a Strategic Network Game with Complex Group Dynamics, by Jonathan Skaggs and Jacob W. Crandall View PDF HTML (experimental) Abstract:Human networks greatly impact important societal outcomes, including wealth and health inequality, poverty, and bullying. As such, understanding human networks is critical to learning how to promote favorable societal outcomes. As a step toward better understanding human networks, we compare and contrast several methods for learning models of human behavior in a strategic network game called the Junior High Game (JHG) [39]. These modeling methods differ with respect to the assumptions they use to parameterize human behavior (behavior matching vs. community-aware behavior) and the moments they model (mean vs. distribution). Results show that the highest-performing method, called hCAB, models the distribution of human behavior rather than the mean and assumes humans use community-aware behavior rather than behavior matching. When applied to small societies, the hCAB model closely mirrors the population dynamics of human groups (with notable differences). Additionally, in a user study, human participants had difficu...
