Visualizing agent based models

Agent based models help us simulate systems with many differnet interacting players. Because these systems are chaotic and nonlinear, it’s hard to capture their dynamics with simple equations (no matter how complex your spreadsheet).

Here are 4 examples of agent-based models, visualized:

1. Conway’s Game of Life shows how very simple agents (cells) can have wildly emergent behaviors from even just a few simple rules.
2. The Washington Post’s Covid-town simulator shows how Covid-19 spreads through a small town of dot-people, helping users see the consequences of exponential growth for themselves.
3. The Radical Dots simulator shows how beliefs spread through a small population of 100 people, to help users understand the dynamics of political echo chambers.
4. Sim City, the classic city simulator, shows how all the interacting people and parts of a stylized city can result in different urban planning outcomes. While agent-based modeling has more serious urban-planning applications, Sim City also reminds us that models can be quite engaging.