Computational Model Library

Model of diffusion of vegetarian diets coupling ABM and argumentation framework

MoPAgrIB model simulates the movement of cultivated patches in a savannah vegetation mosaic ; how they move and relocate through the landscape, depending on farming practices, population growth, social rules and vegetation growth.

Location Analysis Hybrid ABM

Lukasz Kowalski | Published Fri Feb 8 23:43:30 2019

The purpose of this hybrid ABM is to answer the question: where is the best place for a new swimming pool in a region of Krakow (in Poland)?

The model is well described in ODD protocol, that can be found in the end of my article published in JASSS journal (available online: ). Comparison of this kind of models with spatial interaction ones, is presented in the article. Before developing the model for different purposes, area of interest or services, I recommend reading ODD protocol and the article.

I published two films on YouTube that present the model: ,

As an illustration of the utility of agent-based models (ABMs) for poaching mitigation, we developed an exploratory ABM that predicts how interactions between elephants, poachers, and law enforcement affect poaching levels within a virtual protected area. The model is theoretical at this stage but is parameterized with realistic ecological and behavioral data on African elephants, as well as representative information on poaching and ranger strategies. The aim of this model is not to provide a realistic depiction of poaching, but instead to demonstrate how ABMs can bridge the gaps present in the other two main modelling techniques applied to this topic to-date (equation-based and game theoretical models) and to provide a framework for future research. The model provides a starting point for further development and application to real-world situations, perhaps incorporating real GPS data of elephant movements and poaching incidents, and GIS satellite imagery. The aim is for this model to be further developed into a useful management support tool, one that can be used as a virtual laboratory to experiment with different scenarios without putting time, funds, resources, personnel, or elephants at risk.

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