Systematic Review of Agent-Based and System Dynamics Models for Social-Ecological System Case Studies

Abstract

Social–ecological system (SES) modeling involves developing and/or applying models to investigate complex problems arising from the interactions between humans and natural systems. Among the different types, agent-based models (ABM) and system dynamics (SD) are prominent approaches in SES modeling. However, few SES models influence decision-making support and policymaking. The objectives of this study were to explore the application of ABM and SD in SES studies through a systematic review of published real-world case studies and determine the extent to which existing SES models inform policymaking processes. We identified 35 case studies using ABM, SD, or a hybrid of the two and found that each modeling approach shared commonalities that collectively contributed to the policymaking process, offering a comprehensive understanding of the intricate dynamics within SES, facilitating scenario exploration and policy testing, and fostering effective communication and stakeholder engagement. This study also suggests several improvements to chart a more effective trajectory for research in this field, including fostering interdisciplinary collaboration, developing hybrid models, adopting transparent model reporting, and implementing machine-learning algorithms.

On Playing with Emotion: A Spatial Evolutionary Variation of the Ultimatum Game

“…Agent-based models have been developed to study complex systems of diverse nature [ 38 , 39 , 40 , 41 , 42 ]. For instance, agents with emotional states have been used to simulate the emotion contagion [ 43 ] and the emergence of polarization opinion [ 44 ] in online social media and to evaluate a candidate in a selection process [ 45 ].…”