Modeling Evolutionary and Adaptive Systems
Political Science Major (College of Arts & Sciences)
Eduardo Izquierdo (School of Informatics, Computing, & Engineering)
My research involves using computational models to better understand biological, cognitive, and social systems. These models are sometimes referred to as agent-based models and they sometimes involve using evolutionary algorithms and artificial neural networks. This research is highly interdisciplinary, connecting informatics to biology, neuroscience, and cognitive science. Research projects will involve developing and analyzing a computational model of a phenomena of interest to the student. For example, we can focus on developing a computational model of how groups of students learn in a classroom, or a model of segregation in cities, or a model of self-organization in ants, or a model of how cooperation evolves, or a model of voting influence, or a model of gerrymandering, or a model of a biological neural network, or a model of how a neural network can be trained to learn a behavior, etc. We will start by replicating an existing model in the literature and then we will extend the model in new directions.
Technology or Computational Component
Interested students will participate in all aspects of the research process. The student will learn to use Python in order to develop the computational model. In addition to programming skills, this project will involve brainstorming and familiarizing themselves with the literature on a subject of interest.