Abstract: The Study of Complex Systems focuses on understanding complex systems, the internal structure of which is defined by usually various subsystems or individual components (agents), and their nonlinear relationships. With addition of human decisions and activities, the complex human-nature systems are characterized by more complexities such as feedback, multi-finality, and difficulty for prediction. Agent-based modeling (ABM) is a major bottom-up tool to explore the above complexities and has been increasingly used in the past decades. This paper reviews the status quo of ABM in handling complex human-nature systems, and examples will include the agent-based models developed by Chen and Zvoleff in this symposium as well as other people’s related work in the field. Particularly the strengths (e.g., handling feedback and human decisions), weaknesses (e.g., large data demand), and future directions of ABM (e.g., incorporate qualitative analysis) will be highlighted.
Key words: complex systems, coupled natural and human systems, agent-based modeling
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