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.
We also maintain a curated database of over 7500 publications of agent-based and individual based models with 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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We built an agent-based model to foster the understanding of homeowners’ insulation activity.
This agent-based model examines the impact of seasonal aggregation, dispersion, and learning opportunities on the richness and evenness of artifact styles under random social learning (unbiased transmission).
The MML is a hybrid modeling environment that couples an agent-based model of small-holder agropastoral households and a cellular landscape evolution model that simulates changes in erosion/deposition, soils, and vegetation.
The model of market of one commodity , in which there are in each moment of time the same quantity and the same quantity of money was formulated and researched in this text. We also study this system as a game of automata.
This agent-based model represents a stylized inter-organizational innovation network where firms collaborate with each other in order to generate novel organizational knowledge.
Interactions of players embedded in a closed square lattice are determined by distance and overall gains and they lead to shifts of reward payoff between temptation and punishment. A new winner balancing against threats is ultimately discovered.
We construct an agent-based model to investigate and understand the roles of green attachment, engagement in local ecological investment (i.e., greening), and social feedback.
This model is to simulate and compare the admission effects of 3 school matching mechanisms, serial dictatorship, Boston mechanism, and Chinese Parallel, under different settings of information released.
EiLab explores the role of entropy in simple economic models. EiLab is one of several models exploring the dynamics of sustainable economics – PSoup, ModEco, EiLab, OamLab, MppLab, TpLab, and CmLab.
Endogenous social transition from a high-corruption state to a low-corruption state, replication of Hammond 2009
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