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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This is a short NetLogo example demonstrating how to initialize 500 agents with 4 correlated parameters each with random values by doing the necessary calculations in the program “R” and retrieving the results.
This model is used to simulate the influence of spatially and temporally variable sedimentary processes on the distribution of dated archaeological features in a surface context.
The purpose of the model is to explore the impacts of global change on the ability of a community of farmers to adapt their practices to an agricultural pest.
We explore how dynamic processes related to socioeconomic inequality operate to sort students into, and create stratification among, colleges.
The purpose of this curricular model is to teach students the basics of modeling complex systems using agent-based modeling. It is a simple SIR model that simulates how a disease spreads through a population as its members change from susceptible to infected to recovered and then back to susceptible. The dynamics of the model are such that there are multiple emergent outcomes depending on the parameter settings, initial conditions, and chance.
The curricular model can be used with the chapter Agent-Based Modeling in Mixed Methods Research (Moritz et al. 2022) in the Handbook of Teaching Qualitative & Mixed Methods (Ruth et al. 2022).
The instructional videos can be accessed on YouTube: Video 1 (https://youtu.be/32_JIfBodWs); Video 2 (https://youtu.be/0PK_zVKNcp8); and Video 3 (https://youtu.be/0bT0_mYSAJ8).
PolicySpace models public policies within an empirical, spatial environment using data from 46 metropolitan regions in Brazil. The model contains citizens, markets, residences, municipalities, commuting and a the tax scheme. In the associated publications (book in press and https://arxiv.org/abs/1801.00259) we validate the model and demonstrate an application of the fiscal analysis. Besides providing the basics of the platform, our results indicate the relevance of the rules of taxes transfer for cities’ quality of life.
SimAdapt: An individual-based genetic model for simulating landscape management impacts on populations
This purpose of this model is to understand how the coupled demographic dynamics of herds and households constrain the growth of livestock populations in pastoral systems.
Logônia
is a NetLogo model that simulates the growth response of a fictional plant, logônia, under different climatic conditions. The model uses climate data from WorldClim 2.1 and demonstrates how to integrate the LogoClim
model through the LevelSpace
extension.
Logônia
follows the FAIR Principles for Research Software (Barker et al., 2022) and is openly available on the CoMSES Network and GitHub.
A logging agent builds roads based on the location of high-value hotspots, and cuts trees based on road access. A forest monitor sanctions the logger on observed infractions, reshaping the pattern of road development.
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