Integrating Simulation With Agent-Based Modeling To Simulate Human-Ecological Systems

Abstract

This study presents an integrative approach to simulate human-ecological systems by employing computational modeling techniques such as agent-based modeling (ABM), dynamic simulation, and data visualization. The research methodology integrates these techniques to capture the dynamic behavior and heterogeneous characteristics inherent in human-ecological systems. Agent-based modeling is utilized to simulate the behavior of agents representing different entities within the system, including households, firms, patches, and banks. Dynamic simulation techniques are employed to model system-level dynamics and interactions over time, enabling the simulation of key variables such as population dynamics, pollution levels, and activity levels of agents. Data visualization techniques are then used to analyze and visualize simulation outputs, facilitating the interpretation and communication of findings effectively. The results demonstrate the effectiveness of this integrative approach in capturing the complex interactions and dynamics within human-ecological systems. The visualizations produced provide valuable insights into spatial distribution, temporal dynamics, and performance metrics, contributing to a deeper understanding of these systems. Overall, this study highlights the importance of computational modeling and visualization techniques in studying and analyzing complex human-ecological systems, offering valuable implications for decision-making and management within these systems.