Christopher Apelian, PhD

Modeling and Complex Systems

Modeling is how we attempt to understand and adequately represent aspects of our experience. Properly appreciating different model types, their strengths and limitations, their similarities and differences, is important for proper model selection, particularly for problems involving complex systems. In such systems, interacting entities evolve in time, and the modeling of them involves many mathematical, computational, and statistical techniques. One approach currently surging in popularity is agent-based modeling (ABM). ABM utilizes computer simulation of autonomous entities or "agents" that interact with each other and their environment in prescribed ways. The method allows for the study of dynamic processes and their evolution in a manner that differs from more traditional mathematical methods (such as systems of differential equations) in that spatial effects, inhomogeneities, and interactive dynamics are more readily incorporated. The technique provides a computational way to explore problems involving complex dynamics that are often not tractable with traditional mathematical models. (NetLogo is a freely available platform created by Uri Wilensky for developing such models.) I am currently seeking collaborations with researchers in other disciplines to model problems of interest.