The Inspection Model represents a basic food safety system where inspectors, consumers and stores interact. The purpose of the model is to provide insight into an optimal level of inspectors in a food system by comparing three search strategies.

The Inspection Model represents a basic food safety system where inspectors, consumers and stores interact. The purpose of the model is to provide insight into an optimal level of inspectors in a food system by comparing three search strategies.

The model reproduces the spread of environmental awareness among agents and the impact of awareness level of the agents on the consumption of a resource, like energy. An agent is a household with a set of available advanced smart metering functions.

What is stable: the large but coordinated change during a diffusion or the small but constant and uncoordinated changes during a dynamic equilibrium? This agent-based model of a diffusion creates output that reveal insights for system stability.

Simulations based on the Axelrod model and extensions to inspect the volatility of the features over time (AXELROD MODEL & Agreement threshold & two model variations based on the Social identity approach)
The Axelrod model is used to predict the number of changes per feature in comparison to the datasets and is used to compare different model variations and their performance.

Input: Real data

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This model illustrates a positive ‘growth’ feedback loop in which the areal extent of an entity increases through time.

The model investigates conditions, scenarios and strategies for future planning of energy in Egypt, with an emphasis on alternative energy pathways and a sustainable electricity supply mix as part of an energy roadmap till the year 2100. It combines the multi-criteria decision analysis (MCDA) with agent-based modeling (ABM) and Geographic Information Systems (GIS) visualization to integrate the interactions of the decisions of multi-agents, the multi-criteria evaluation of sustainability, the time factor and the site factors to assess the transformation of energy landscapes.

MHCABM is an agent-based, multi-hazard risk interaction model with an integrated applied dynamic adaptive pathways planning component. It is designed to explore the impacts of climate change adaptation decisions on the form and function of a coastal human-environment system, using as a case study an idealised patch based representation of the Mount North-Omanu area of Tauranga city, New Zealand. The interacting hazards represented are erosion, inundation, groundwater intrusion driven by intermittent heavy rainfall / inundations (storm) impacts, and sea level rise.

A flexible framework for Agent-Based Models (ABM), the ‘epiworldR’ package provides methods for prototyping disease outbreaks and transmission models using a ‘C++’ backend, making it very fast. It supports multiple epidemiological models, including the Susceptible-Infected-Susceptible (SIS), Susceptible-Infected-Removed (SIR), Susceptible-Exposed-Infected-Removed (SEIR), and others, involving arbitrary mitigation policies and multiple-disease models. Users can specify infectiousness/susceptibility rates as a function of agents’ features, providing great complexity for the model dynamics. Furthermore, ‘epiworldR’ is ideal for simulation studies featuring large populations.

This is a first preliminary simulation model to model segregation in the city of Salzburg, Austria.