Comparing 7 alternative models of human behavior and assess their performance on a high resolution dataset based on individual behavior performance in laboratory experiments.

This is a model of innovation implementation inside an organization. It characterizes an innovation as a set of distributed and technically interdependent tasks performed by a number of different and socially interconnected frontline workers.

In this model, we simulate the navigation behavior of homing pigeons. Specifically we use genetic algorithms to optimize the navigation and flocking parameters of pigeon agents.

We construct an agent-based model to investigate and understand the roles of green attachment, engagement in local ecological investment (i.e., greening), and social feedback.

The model simulates interactions in small, task focused groups that might lead to the emergence of status beliefs among group members.

A general model of human mate choice in which agents are localized in space, interact with close neighbors, and tend to range either near or far. At the individual level, our model uses two oft-used but incompletely understood decision rules: one based on preferences for similar partners, the other for maximally attractive partners.

This agent-based model simulates the diffusion of a social change process stratified by social class in space and time which is solely driven social and spatial variation in communication links.

Positive feedback can lead to “trapping” in local optima. Adding a simple negative feedback effect, based on ant behaviour, prevents this trapping

CHALMS simulates housing and land market interactions between housing consumers, developers, and farmers in a growing ex-urban area.

This model simulates the dynamics of eighteenth-century infantry battle tactics. The goal is to explore the effect of different tactics and individual traits in the dynamics of the combat.