The purpose of this project is to develop a model of residential mobility, built to simulate individual households, their perception and reaction to varying conditions across different scales of interaction, and their movements to occupy housing in a physical, social, and economic environment. The methodology underpinning the model is based on an automata core, leveraging the advantages it offers in terms of representing individual entities and their rule-based interactions. This methodology is extended, however, to incorporate geography-specific functionality, with advantages for modeling human systems. The applicability of the methodology is demonstrated through the development of a rich model of residential mobility, in which individual households interact with other households and real estate infrastructure, dynamically in space and time, to form synthetic communities and artificial property submarkets. Use of the model for what-if experimentation is demonstrated with synthetic economic and socio-demographic simulation scenarios.

The classic Schelling segreation model, run with (a) 8,000 households with 10% tolerance, (b) 8,000 households with 30% tolerance, (c) 8,000 households with 40% tolerance. (Agents are black or gray; free space is white. t denotes iterations of the simulation.)

Hierarchical treatment of entities (geographic automata) in the simulation

Relocating and settled agents organize their preferences by motivation and scale in the simulation

The GUI for the model during a simulation run. It's not that sophisticated in visualization terms, but it shows the rich level of detail in the model.

A toolkit for measuring sprawl

Modeling time, space, and behavior

Simulating crowd behavior

Wi-Fi mapping and geography