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 model explores food distribution patterns that emerge in artificial small-scale human groups when agents follow a set of spatially explicit sharing interaction rules derived from a theory on the evolution of the egalitarian social instinct.
The model is then used for assessing three hypothetical and contrasted infrastructure-oriented adaptation strategies for the winter tourism industry, that have been previously discussed with local stakeholders, as possible alternatives to the “business-as-usual” situation.
How does the world population adapt its policies on energy when it is confronted with a climate change? This model combines a climate-economy model with adaptive agents.
The original Ache model is used to explore different distributions of resources on the landscape and it’s effect on optimal strategies of the camps on hunting and camp movement.
The MOBILITY model analyzes how agents’ mobility affects the performance of social-ecological systems in different landscape configurations.
This is model that simulates how multiple kinds of peer effects shape the diffusion of innovations through different types of social relationships.
A discrete-time stochastic model with state-dependent transmission probabilities and multi-agent simulations focusing on possible risks that could materialize in the final phase of the epidemic.
This model can be used to explore under which conditions agents behave as observed in field experiments on irrigation games.
Lakeland 2 is a simple version of the original Lakeland of Jager et al. (2000) Ecological Economics 35(3): 357-380. The model can be used to explore the consequences of different behavioral assumptions on resource and social dynamics.
This is a replication of the Pumpa model that simulates the Pumpa Irrigation System in Nepal (Cifdaloz et al., 2010).
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