Our mission is to help computational modelers at all levels engage in the establishment and adoption of community standards and good practices for developing and sharing computational models. Model authors can freely publish their model source code in the Computational Model Library alongside narrative documentation, open science metadata, and other emerging open science norms that facilitate software citation, reproducibility, interoperability, and reuse. Model authors can also request peer review of their computational models to receive a DOI.
All users of models published in the library must cite model authors when they use and benefit from their code.
Please check out our model publishing tutorial and contact us if you have any questions or concerns about publishing your model(s) in the Computational Model Library.
We also maintain a curated database of over 7500 publications of agent-based and individual based models with additional detailed metadata on availability of code and bibliometric information on the landscape of ABM/IBM publications that we welcome you to explore.
Displaying 6 of 36 results agriculture clear search
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.
To investigate the potential of using Social Psychology Theory in ABMs of natural resource use and show proof of concept, we present an exemplary agent-based modelling framework that explicitly represents multiple and hierarchical agent self-concepts
A model for simulating farmers and foresters response on changing climate and changing socio-economic parameters. Modeled are changes in land-use as well as in ecosystem services provision.
An agent-based model to investigate the history of irrigated agriculture in the Upper Guadiana Basin, Spain, in order to learn about the influence of farmers’ characteristics (inter alia profit orientation, risk aversion, skills, available labour force and farm size) on land-use change and associated groundwater over-use in this region.
This is an empirical model described in http://dx.doi.org/10.1016/j.landurbplan.2010.05.001. The objective of the model is to simulate how the decision-making of farmers/agents with different strategies can affect the landscape structure in a region in the Netherlands.
Swidden Farming is designed to explore the dynamics of agricultural land management strategies.
Displaying 6 of 36 results agriculture clear search