Moving to Agent-Based Modeling

Given the caveats we outlined re: macro-level voting modeling, we’re moving on to a totally different approach. Using something called agent-based modeling (ABM), we’re hoping to move to a point where we can both predict elections, but also use the system to conduct studies on the effectiveness of various election models.

ABM can be defined simply as an individual-centric approach to model design, and has become widespread in multiple fields, from biology to economics. In such models, researchers define agents (e.g., voters, candidates, and media) each with various properties, and an environment in which such agents can behave and interact.

Examining systems through ABM seeks to answer four questions:

• Empirical: What are the (causal) explanations for how systems evolve?
• Heuristic: What are outcomes of (even simple) shocks to the system?
• Method: How can we advance our understanding of the system?
• Normative: How can systems be designed better?

We'll start to provide updates on our progress on the development on our system in the coming weeks.