Social emergence in complex adaptive systems: a systematic review using agent-based simulation
Keywords:
Social emergency, Complex Adaptive Systems, agent-based simulation, self-organization, nonlinear modelsAbstract
Introduction: Social emergence is a central phenomenon for understanding the dynamics and organization of contemporary societies, especially when studied through the lens of complex adaptive systems. Objective: To critically analyze the mechanisms of social emergence in complex adaptive systems using agent-based models, assessing their ability to explain nonlinear phenomena. Materials and Methods: A PRISMA systematic review of 66 studies (2010–2025) in Scopus, Web of Science, SciELO, Redalyc, and arXiv. Results: Social emergence arises from simple local rules that generate unpredictable global patterns (segregation, social norms). Discussion: ABMs theoretically validate self-organization in complex adaptive systems, but face predictive and reductionist limitations. Cases such as Schelling’s model demonstrate their heuristic usefulness. Conclusions: ABMs are valuable tools for exploring social complexity, but require integration with qualitative approaches and advances in AI to overcome epistemological challenges.
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