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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What is it?
This model demonstrates a very simple bidding market where buyers try to acquire a desired item at the best price in a competitive environment
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This is a series of simulations of binary group decisions and the outcomes applied to a generalized version of Price’s Equation for system fitness.
The model attempts to explore the trade-offs between immigration policies and successfully identifying human trafficking victims.
The objective of this study is to create a framework to simulate and analyze the effect of multiple business scenarios on the adoption behavior of a group of technology products.
CRESY-I stands for CREativity from a SYstems perspetive, Model I. This is the base model in a series designed to describe a systems approach to creativity in terms of variation, selection and retention (VSR) subprocesses.
The set of models test how receivers ability to accurately rank signalers under various ecological and behavioral contexts.
The (cultural) evolution of cooperative breeding in harsh environments.
More frequently protests are accompanied by an opposing group performing a counter protest. This phenomenon can increase tension such that police must try to keep the two groups separated. However, what is the best strategy for police? This paper uses a simple agent-based model to determine the best strategy for keeping the two groups separated. The ‘thin blue line’ varies in density (number of police), width and the keenness of police to approach protesters. Three different groups of protesters are modelled to mimic peaceful, average and volatile protests. In most cases, a few police forming a single-file ‘thin blue line’ separating the groups is very effective. However, when the protests are more volatile, it is more effective to have many police occupying a wide ‘thin blue line’, and police being keen to approach protesters. To the authors knowledge, this is the first paper to model protests and counter-protests.
We provide an agent-based model of collective action, informed by Granovetter (1978) and its replication model by Siegel (2009). We use the model to examine the role of ICTs in collective action under different cultural and political contexts.
ACT is an ABM based on an existing conceptualisation of the concept of critical transitions applied to the energy transition. With the model we departed from the mean-field approach simulated relevant actor behaviour in the energy transition.
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