An artifcal stock market model that allows users to vary the number of risky assets as well as the network topology that investors forms in an attempt to understand the dynamics of the market.

This model makes it possible to explore how network clustering and resistance to changing existing status beliefs might affect the spontaneous emergence and diffusion of such beliefs as described by status construction theory.

This model allows for analyzing the most efficient levers for enhancing the use of recycled construction materials, and the role of empirically based decision parameters.

Implemented as a virtual laboratory, this model explores transitions in land-use and livelihood decisions that emerge from changing local and global conditions.

This multi-model (i.e. a model composed of interacting submodels) is a multi-level representation of a collective motion phenomenon. It was designed to study the impact of the mutual influences between individuals and groups in collective motion.

LimnoSES is a coupled system dynamics, agent-based model to simulate social-ecological feedbacks in shallow lake use and management.

The Agent-Based Wildfire Simulation Environment (ABWiSE) translates the concept of a moving fire front as a set of mobile fire agents that respond to, and interact with, vegetation, wind, and terrain. Presently, the purpose of ABWiSE is to explore how ABM, using simple interactions between agents and a simple atmospheric feedback model, can simulate emergent fire spread patterns.

Complete Library for object oriented development of Classifier Systems. See for the concept behind.

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.

This agent-based model simulates how new immigrant households choose where to live in Metro Vancouver under the origins diversity scenario. The model begins with 16,000 household agents, reflecting an expected annual population increase of about 42,500 people based on an average household size of 2.56. Each agent is assigned four characteristics: one of ten origin categories, income level (adjusted using NOC data and recent immigrant earnings), likelihood of having children, and preferred mode of commuting. The ten origin groups are drawn from Census patterns, including six subgroups within the broader Asian category (China, India, the Philippines, Iran, South Korea, and Other Asian countries) and two categories for immigrants from the Americas. This refined classification better captures the diversity of newcomers arriving in the region.