Behavioral alignment in social networks
Yu Xia, Alex McAvoy, Qi Su

TL;DR
This paper investigates how simple local behavioral rules and network structures influence the emergence, stability, and complexity of collective behaviors like coordination and anti-coordination in social networks.
Contribution
It introduces an analysis of self-exploration based behavioral models in networked systems, revealing the exponential growth of equilibria and the impact of network structure on dynamics.
Findings
Number of equilibria can grow exponentially with network changes
Network structure significantly affects equilibrium time
Average path length captures key behavioral dynamics
Abstract
The orderly behaviors observed in large-scale groups, such as fish schooling and the organized movement of crowds, are both ubiquitous and essential for the survival and stability of these systems. Understanding how such complex collective behaviors emerge from simple local interactions and behavioral adjustments is a significant scientific challenge. Historically, research has predominantly focused on imitation and social learning, where individuals adopt the strategies of more successful peers to refine their behavior. However, in recent years, an alternative learning approach based on self-exploration and introspective learning has garnered increasing attention. In this paradigm, individuals assess their own circumstances and select strategies that best align with their specific conditions. Two examples are coordination and anti-coordination, where individuals align with and diverge…
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