Abstract

In recent years, agent-based modeling has captured considerable attention from researchers across diverse fields. This surge of interest stems from the fact that this computational approach enables the simultaneous modeling of multiple individual agents in a virtual environment, thus making it a promising tool for investigating complex climate-change related phenomena. Understanding such phenomena and designing effective interventions require the integration of knowledge from various disciplines: Notably, psychological research plays a crucial role, given its centrality in understanding human cognition and behavior. Agent-based models, with their capacity to simulate both populations and their environments, are uniquely suited for this purpose. In this work, we provide a concise overview of agent-based modeling, outlining its features and advantages. Then, we delve into the applications of this computational approach in studying climate-change related phenomena, with a particular emphasis on the valuable contribution of psychological research. As illustrative examples, we examine how agent-based models have been employed to enhance flood risk estimations. By combining engineering expertise with psychological theories and data, these models can capture more accurately the severity of the final outcomes of flood events, which might be significantly influenced by human behavior. In conclusion, we highlight potential future directions aimed at optimizing the implementation of such models.