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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This model is used to simulate the influence of spatially and temporally variable sedimentary processes on the distribution of dated archaeological features in a surface context.
SimAdapt: An individual-based genetic model for simulating landscape management impacts on populations
The functioning of an hospital ED. The use case concerns an hospital in Italy which is moving in a new building. Simulations interest both new and old department, to investigate changes by exploring KPIs.
This model allows for the investigation of the effect spatial clustering of raw material sources has on the outcome of the neutral model of stone raw material procurement by Brantingham (2003).
This model simulates a foraging system based on Middle Stone Age plant and shellfish foraging in South Africa.
This agent-based model using ‘Blanche’ software provides policy-makers with a simulation-based demonstration illustrating how autonomous agents network and operate complementary systems in a decentral
This model studies the emergence and dynamics of generalized trust. It does so by modeling agents that engage in trust games and, based on their experience, slowly determine whether others are, in general, trustworthy.
We build a computational model to investigate, in an evolutionary setting, a series of questions pertaining to happiness.
This theoretical model includes forested polygons and three types of agents: forest landowners, foresters, and peer leaders. Agent rules and characteristics were parameterized from existing literature and an empirical survey of forest landowners.
The model simulates the process of widespread diffusion of something due to popularity (i.e., bandwagon) within an organization.
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