This ABM looks at the effect of multiple reviewers and their behavior on the quality and efficiency of peer review. It models a community of scientists who alternatively act as “author” or “reviewer” at each turn.

The model analyzes the economic and ecological effects of a provision of livestock drought insurance for dryland pastoralists. More precisely, it yields qualitative insights into how long-term herd and pasture dynamics change through insurance.

The Agent-Based Ramsey growth model is designed to analyze and test a decentralized economy composed of utility maximizing agents, with a particular focus on understanding the growth dynamics of the system. We consider farms that adopt different investment strategies based on the information available to them. The model is built upon the well-known Ramsey growth model, with the introduction of endogenous technical progress through mechanisms of learning by doing and knowledge spillovers.

Swidden Farming is designed to explore the dynamics of agricultural land management strategies.

An algorithm implemented in NetLogo that can be used for searching resources.

The Retail Competition Agent-based Model (RC-ABM) is designed to simulate the retail competition system in the Region of Waterloo, Ontario, Canada, which which explicitly represents store competition behaviour. Through the RC-ABM, we aim to answer 4 research questions: 1) What is the level of correspondence between market share and revenue acquisition for an agent-based approach compared to a traditional location-allocation-based approach? 2) To what degree can the observed store spatial pattern be reproduced by competition? 3) To what degree are their path dependent patterns of retail success? 4) What is the relationship between retail survival and the endogenous geographic characteristics of stores and consumer expenditures?

Communication processes occur in complex dynamic systems impacted by person attitudes and beliefs, environmental affordances, interpersonal interactions and other variables that all change over time. Many of the current approaches utilized by Communication researchers are unable to consider the full complexity of communication systems or the over time nature of our data. We apply agent-based modeling to the Reinforcing Spirals Model and the Spiral of Silence to better elucidate the complex and dynamic nature of this process. Our preliminary results illustrate how environmental affordances (i.e. social media), closeness of the system and probability of outspokenness may impact how attitudes change over time. Additional analyses are also proposed.

GenoScope is a modular agent-based model designed to simulate how cells respond to environmental stressors or other treatment conditions across species. Genes, treatment conditions, and cell physiology outcomes are represented as interacting agents that influence each other’s behavior over time. Rather than imposing fixed interaction rules, GenoScope initializes with randomized regulatory logic and calibrates rule sets based on empirical data. Calibration is grounded in a common-garden experiment involving 16 mammalian species—including humans, dolphins, bats, and camels—exposed to varying levels of temperature, glucose, and oxygen. This comparative approach enables the identification of mechanisms by which animal cells achieve robustness under extreme environmental conditions.

This model simulates household water consumption patterns in an urban environment. Its current setup compares monthly water consumption data, and the results of a daily heuristic water demand model with the simulation results produced by household demographics that is fine tuned via some base demand model. It’s designed to estimate and analyze water demand based on various factors including household demographics, daily routines of residents (working, weekending, vacation patterns), weather conditions (temperature and precipitation), appliance usage patterns, seasonal variations, and special periods such as weekends and holidays. The model aims to help understand how different factors influence residential water consumption and can be used for water demand forecasting and management.

We develop a spatial, evolutionary model of the endogenous formation and dissolution of groups using a renewable common pool resource. We use this foundation to measure the evolutionary pressures at different organizational levels.