Exploring how learning and social-ecological networks influence management choice set and their ability to increase the likelihood of species coexistence (i.e. biodiversity) on a fragmented landscape controlled by different managers.

A proof-of-concept agent-based model ‘SimDrink’, which simulates a population of 18-25 year old heavy alcohol drinkers on a night out in Melbourne to provide a means for conducting policy experiments to inform policy decisions.

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.

The Pampas Model is an Agent-Based Model intended to explore the dynamics of structural and land use changes in agricultural systems of the Argentine Pampas in response to climatic, technological economic, and political drivers.

This code can be used to analyze the sensitivity of the Deffuant model to different measurement errors. Specifically to:
- Intrinsic stochastic error
- Binning of the measurement scale
- Random measurement noise
- Psychometric distortions

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The model objective’s is to explore the management choice set to uncover which subsets of strategies are most effective at maximizing species coexistence on a fragmented landscape.

The MML is a hybrid modeling environment that couples an agent-based model of small-holder agropastoral households and a cellular landscape evolution model that simulates changes in erosion/deposition, soils, and vegetation.

This model is represents an effort to replicate one of the first attempts (van der Vaart 2006) to develop an agent based model of agricultural origins using principles and equations drawn from human behavioral ecology. We have taken one theory of habitat choice (Ideal Free Distribution) and applied it to human behavioral adaptations to differences in resource quality of different habitats.

This model grows land use patterns that emerge as a result of land-use compatibilities stablished in urban development plans, land topography, and street networks. It contains urban brushes to paint streets and land uses as a way to learn about urban pattern emergence through free experimentation.

The Communicating Hazard Information in the Modern Environment (CHIME) agent-based model (ABM) is a Netlogo program that facilitates the analysis of information flow and protective decisions across space and time during hazardous weather events. CHIME ABM provides a platform for testing hypotheses about collective human responses to weather forecasts and information flow, using empirical data from historical hurricanes. The model uses real world geographical and hurricane data to set the boundaries of the simulation, and it uses historical hurricane forecast information from the National Hurricane Center to initiate forecast information flow to citizen agents in the model.