## Department Colloquium

### Friday, February 5th, 2021

**Time:** 2:30 p.m. **Place:** Online (via Zoom)

**Speaker:** David Banks (Duke University)

**Title:** Statistical Challenges in Agent-Based Models.

**Abstract: ** Agent-based models (ABMs) are computational models used to simulate the actions and interactions of agents within a system. Usually, each agent has a relatively simple set of rules for how it responds to its environment and to other agents. These models are used to gain insight into the emergent behavior of complex systems with many agents, in which the emergent behavior depends upon the micro-level behavior of the individuals. ABMs are widely used in many fields, and this talk reviews some of those applications. However, as relatively little work has been done on statistical theory for such models, this talk also points out some of those gaps and recent strategies to address them.

**David Banks** is a Professor of the Practice of Statistics at Duke University. His research areas include models for dynamic networks, dynamic text networks, adversarial risk analysis, human rights statistics, agent-based models, forensics, and certain topics in high-dimensional data analysis. He is past-president of the Classification Society, and has twice served on the Board of Directors of the American Statistical Association. He is currently the president of the International Society for Business and Industrial Statistics. He is a fellow of the American Statistical Association and of the Institute of Mathematical Statistics. He won the American Statistical Association's Founders Award in 2015.