Our mission is to help computational modelers develop, document, and share their computational models in accordance with community standards and good open science and software engineering practices. Model authors can publish their model source code in the Computational Model Library with narrative documentation as well as metadata that supports open science and emerging norms that facilitate software citation, computational reproducibility / frictionless reuse, and interoperability. Model authors can also request private peer review of their computational models. Models that pass peer review receive a DOI once published.
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 feel free to contact us if you have any questions or concerns about publishing your model(s) in the Computational Model Library.
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Model of shifting cultivation. All parameters can be controlled by the user or the model can be run in adaptive mode, in which agents innovate and select parameters.
CHALMS simulates housing and land market interactions between housing consumers, developers, and farmers in a growing ex-urban area.
This is an empirically calibrated agent-based model that replicates spruce-budworm outbreaks, one of the most cited adaptive cycles reported. The adaptive-cycle metaphor by L. H. Gunderson and C. S. Holling posits the cross-case existence of repeating cycles of growth, conservation, collapse, and renewal in many complex systems, triggered by loss of resilience. This model is one of the first agent-based models of such cycles, with the novelty that adaptive cycles are not defined by system- […]
An ABM, derived from a case study and a series of surveys with greenhouse growers in the Westland, Netherlands. Experiments using this model showshow that the greenhouse horticulture industry displays diversity, adaptive complexity and an uneven distribution, which all suggest that the industry is an evolving system.
The WaterScape is an agent-based model of the South African water sector. This version of the model focuses on potential barriers to learning in water management that arise from interactions between human perceptions and social-ecological system conditions.
In this model agents meet, evaluate one another, decide whether or not to date, if and when to become sexual partners, and when to break up.
This model studies the effect of the agents’ adaptive expectation on cooperation frequency in the prisoner’s dilemma game in complex networks from an agent based approach. The model is implemented in Repast simphony 1.2.
The model aims to mimic the observed behavior of participants in spatially explicit dynamic commons experiments.
Agent-based model using Blanche software 4.6.5. Blanche software is included in the dataset file.
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