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 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 Mobility Transition Model (MoTMo) is a large scale agent-based model to simulate the private mobility demand in Germany until 2035. Here, we publish a very much reduced version of this model (R-MoTMo) which is designed to demonstrate the basic modelling ideas; the aim is by abstracting from the (empirical, technological, geographical, etc.) details to examine the feed-backs of individual decisions on the socio-technical system.
This is the R code of the mathematical model that includes the decision making formulations for artificial agents. This code corresponds to equations 1-70 given in the paper “A Mathematical Model of The Beer Game”.
This is the R code of the mathematical model that includes the decision making formulations for artificial agents. Plus, the code for graphical output is also added to the original code.
This is the R code of the mathematical model used for verification. This code corresponds to equations 1-9, 15-53, 58-62, 69-70, and 72-75 given in the paper “A Mathematical Model of The Beer Game”.
the model can be used to describe the product diffusion in an Advance Selling Strategy. this model takes into account the consumers product adoption, and describe consumer’s online behavior based on four states.
This is the full repository to run the survival analysis (in R) and run the population viability model and its analysis (NetLogo + R) of the Northern Bald Ibis (NBI) presented in the study
On the road to self-sustainability: Reintroduced migratory European Northern Bald Ibises (Geronticus eremita) still need management interventions for population viability
by Sinah Drenske, Viktoriia Radchuk, Cédric Scherer, Corinna Esterer, Ingo Kowarik, Johannes Fritz, Stephanie Kramer-Schadt
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This is a short NetLogo example demonstrating how to initialize 500 agents with 4 correlated parameters each with random values by doing the necessary calculations in the program “R” and retrieving the results.
The purpose of this model is to illustrate the use of agent-based computational modelling in the study of the emergence of reputation and status beliefs in a population.
Knowledge Space model of Opinion Dynamics.
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