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.
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The basic premise of the model is to simulate several ‘agents’ going through build-buy cycles: Build: Factories follow simple rules of strategy in the allocation of resources between making exploration and exploitation type products. Buy: Each of two types of Consumers, early-adopters and late adopters, follow simple purchase decision rules in deciding to purchase a product from one of two randomly chosen factories. Thus, the two working ‘agents’ of the model are ‘factories’ and […]
The purpose of this model is to analyze the dynamics of endogenously created oscillations in housing prices using a system dynamics simulation model, built from the perspective of construction companies.
This is a multi-patch meta-population ecological model. It intended as a test-bed in which to test the impact of humans with different kinds of social structure.
This is a complex “Data Integration Model”, following a “KIDS” rather than a “KISS” methodology - guided by the available evidence. It looks at the complex mix of social processes that may determine why people vote or not.
The purpose of this model is to examine equity and efficiency in crop production across a system of irrigated farms, as a function of maintenance costs, assessed water fees, and the capacity of farmers to trade water rights among themselves.
The modeling includes citizens, bounded into families; firms and governments; all of them interacting in markets for goods, labor and real estate. The model is spatial and dynamic.
The model represents an archetypical fishery in a co-evolutionary social-ecological environment, capturing different dimensions of trust between fishers and fish buyers for the establishment and persistence of self-governance arrangements.
This model simulates networking mechanisms of an empirical social network. It correlates event determinants with place-based geography and social capital production.
Our societal belief systems are pruned by evolution, informing our unsustainable economies. This is one of a series of models exploring the dynamics of sustainable economics – PSoup, ModEco, EiLab, OamLab, MppLab, TpLab, CmLab.
Model explains both the final state and the dynamics of the development process of the wine sector in the Małopolska region in Poland. Model admits heterogeneous agents (regular farms,large and small vineyards).
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