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 (cultural) evolution of cooperative breeding in harsh environments.
Dynamic bipartite network model of agents and games in which agents can participate in multiple public goods games.
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).
A dynamic model of social network formation on single-layer and multiplex networks with structural incentives that vary over time.
This model explores a price Q-learning mechanism for perishable products that considers uncertain demand and customer preferences in a competitive multi-agent retailer market (a model-free environment).
The purpose of this model is to explore the effects of different power structures on a cross-functional team’s prosocial decision making. Are certain power distributions more conducive to the team making prosocial decisions?
Local scale mobility, namely foraging, leads to global population dispersal. Agents acquire information about their environment in two ways, one individual and one social. See also http://www.openabm.org/model/3846/
This model demonstrates how to illustrate a cluster pattern by counting turtles within i moving circle with a specified radius. The procedure is common in archaeological spatial analysis.
This agent-based model explores the existence of positive feedback loops related to illegal, unregulated, unreported (IUU) fishing; the use of forced labor; and the depletion of fish populations due to commercial fishing.
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.
Displaying 10 of 1207 results