A team of researchers at Michigan Technological University is harnessing the computing muscle behind the leading video games to understand the most intricate of real-life systems.
Led by Roshan D'Souza, the group has supercharged agent-based modeling, a powerful but computationally massive forecasting technique, by using the graphic processing units which drive the spectacular imagery beloved of video gamers. In particular, the team aims to model complex biological systems, such as the human immune response to a tuberculosis bacterium.
Agent-based modeling simulates the behaviors of complex systems. It can be used to predict the outcomes of anything from pandemics to the price of pork bellies. It is, as the name suggests, based on individual agents: e.g., sick people and well people, predators and prey, etc. It applies rules that govern how those agents behave under various conditions, sets them loose, and tracks how the system changes over time. The outcomes are unpredictable and can be as surprising as real life.