Darren Schreiber is currently a Senior Lecturer in Politics at the University of Exeter, his previous appointments were at Central European University in Budapest, Hungary; University of California, San Diego; and the University of Pennsylvania. His research centers on emergence and complexity in political systems. In his first career as an attorney, Darren specialized in federal litigation and had his first federal jury trial at age 23. While earning his Ph.D. in Political Science at UCLA, Darren developed an agent-based computer simulation of the formation and dynamics of political parties. He has pioneered the subfield of neuropolitics with the first use of functional brain imaging (fMRI) to study the neural foundations of politics.

Day 1 — Foundations
What is an Agent Based Model?
Why Agent Based Models?
Introduction to Emergence and Complexity
Introduction to NetLogo
Simple Models
John Conway’s Game of Life
Simple Economy
Introduction to designing your own social science models

Day 2 — Building a Simple Model
Modeling principles
The Cocktail Party Model
The Schelling Segregation Model

Session 3 — Extending Models
Schelling Segregation Model Extended
Multiple Ethnicities
Diverse preferences
Individuals who prefer diversity

Session 4 — Creating Your Own Model
Agents’ Properties and Behaviors
Environments
Interactions
Scheduling

Session 5 — Understanding Your Model
Analyzing Agent-Based Models
Trace analysis
Statistical analysis
Verification, Validation, and Replication