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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REHAB has been designed as an ice-breaker in courses dealing with ecosystem management and participatory modelling. It helps introducing the two main tools used by the Companion Modelling approach, namely role-playing games and agent-based models.
The model reproduces the spread of environmental awareness among agents and the impact of awareness level of the agents on the consumption of a resource, like energy. An agent is a household with a set of available advanced smart metering functions.
We develop a spatial, evolutionary model of the endogenous formation and dissolution of groups using a renewable common pool resource. We use this foundation to measure the evolutionary pressures at different organizational levels.
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 CONSERVAT model evaluates the effect of social influence among farmers in the Lake Naivasha basin (Kenya) on the spatiotemporal diffusion pattern of soil conservation effort levels and the resulting reduction in lake sedimentation.
The purpose of the model is to simulate the cultural hitchhiking hypothesis to explore how neutral cultural traits linked with advantageous traits spread together over time
We used a computer simulation to measure how well different network structures (fully connected, small world, lattice, and random) find and exploit resource peaks in a variable environment.
This agent-based model represents a stylized inter-organizational innovation network where firms collaborate with each other in order to generate novel organizational knowledge.
This model simulates the lithic raw material use and provisioning behavior of a group that inhabits a permanent base camp, and uses stone tools.
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