This model is used to simulate the influence of spatially and temporally variable sedimentary processes on the distribution of dated archaeological features in a surface context.

MIOvPOPsurveillance is set up to simulate harvest-based chronic wasting disease (CWD) surveillance of white-tailed deer (Odocoileus virginianus) populations in select Michigan Counties. New regions can be readily added, also the model can be readily adapted for other disease systems and used for informed-decision making during planning and implementation stages of disease surveillance in wildlife and free-ranging species.

Demand planning requires processing of distributed information. In this process, individuals, their properties and interactions play a crucial role. This model is a computational testbed to investigate these aspects with respect to forecast accuracy.

This model simulates different farmers’ decisions and actions to adapt to the water scarce situation. This simulation helps to investigate how farmers’ strategies may impact macro-behavior of the social-ecological system i.e. overall groundwater use change and emigration of farmers. The environmental variables’ behavior and behavioral rules of stakeholders are captured with Fuzzy Cognitive Map (FCM) that is developed with both qualitative and quantitative data, i.e. stakeholders’ knowledge and empirical data from studies. This model have been used to compare the impact of different water scarcity policies on overall groundwater use in a farming community facing water scarcity.

Model of shifting cultivation. All parameters can be controlled by the user or the model can be run in adaptive mode, in which agents innovate and select parameters.

The purpose of this model is to enhance a basic ABM through a simple set of rules identified using the activity-driven models in order to produce more realistic patterns of pedestrian movement.

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

An agent-based model designed as a tool to assess and plan free-ranging dog population management programs that implement Animal Birth Control (ABC). The time, effort, financial resources and conditions needed to successfully control dog populations and achieve rabies control can be determined by performing virtual experiments using DogPopDy.

An extension of Epstein’s (2002) model for civil violence and Fonoberova et al’s (2012) extension of Epstein’s model. Uses heterogeneous hardship values and dynamic legitimacy values. Models public funding decisions between police and social welfare.

The Non-Deterministic model of affordable housing Negotiations (NoD-Neg) is designed for generating hypotheses about the possible outcomes of negotiating affordable housing obligations in new developments in England. By outcomes we mean, the probabilities of failing the negotiation and/or the different possibilities of agreement.
The model focuses on two negotiations which are key in the provision of affordable housing. The first is between a developer (DEV) who is submitting a planning application for approval and the relevant Local Planning Authority (LPA) who is responsible for reviewing the application and enforcing the affordable housing obligations. The second negotiation is between the developer and a Registered Social Landlord (RSL) who buys the affordable units from the developer and rents them out. They can negotiate the price of selling the affordable units to the RSL.
The model runs the two negotiations on the same development project several times to enable agents representing stakeholders to apply different negotiation tactics (different agendas and concession-making tactics), hence, explore the different possibilities of outcomes.
The model produces three types of outputs: (i) histograms showing the distribution of the negotiation outcomes in all the simulation runs and the probability of each outcome; (ii) a data file with the exact values shown in the histograms; and (iii) a conversation log detailing the exchange of messages between agents in each simulation run.