This model aims to investigate how different type of learning (social system) and disturbance specific attributes (ecological system) influence adoption of treatment strategies to treat the effects of ecological disturbances.

The model explores the impact of journal metrics (e.g., the notorious impact factor) on the perception that academics have of an article’s scientific value.

MOOvPOP is designed to simulate population dynamics (abundance, sex-age composition and distribution in the landscape) of white-tailed deer (Odocoileus virginianus) for a selected sampling region.

This model simulates networking mechanisms of an empirical social network. It correlates event determinants with place-based geography and social capital production.

MOOvPOPsurveillance was developed as a tool for wildlife agencies to guide collection and analysis of disease surveillance data that relies on non-probabilistic methods like harvest-based sampling.

Butterflies (turtles) goes through metamorphism and moves to corresponding patches each season of the year. The number of years and seasons are monitored.

The purpose of this model is to better understand the dynamics of a multihost pathogen in two host system comprising of high densities of domestic hosts and sympatric wildlife hosts susceptible to the pathogen.

The model aims at simulating the car traffic. It allows to use either a macro or a micro sub-model for the simulation of the flow on the roads.

We present an Agent-Based Stock Flow Consistent Multi-Country model of a Currency Union to analyze the impact of changes in the fiscal regimes that is permanent changes in the deficit-to-GDP targets that governments commit to comply.

This is a simulation model of an intelligent agent that has the objective to learn sustainable management of a renewable resource, such as a fish stock.