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.
Displaying 10 of 20 results demography clear search
This model examines the potential impact of market collapse on the economy and demography of fishing households in the Logone Floodplain, Cameroon.
The model examines the dynamics of herd growth in African pastoral systems. We used it to examine the role of scale (herd size) stochasticity (in mortality, fertility, and offtake) on herd growth.
This model illustrates how the effective population size and the rate of change in mean skill level of a cultural trait are affected by the presence of natural selection and/or the cultural transmission mechanism by which it is passed.
The simulation model conducts fine-grained population projection by specifying life course dynamics of individuals and couples by means of traditional demographic microsimulation and by using agent-based modeling for mate matching.
ForagerNet3_Demography_V2 is a non-spatial ABM for exploring hunter-gatherer demography. This version (developed from FN3D_V1) contains code for calculating the ratio of old to young adults (the “OY ratio”) in the living and dead populations.
ForagerNet3_Demography is a non-spatial ABM for exploring hunter-gatherer demography. Key methods represent birth, death, and marriage. The dependency ratio is an imporant variable in many economic decisions embedded in the methods.
A reimplementation of the Wedding Ring model by Francesco Billari. We investigate partnership formation in an agent-based framework, and combine this with statistical demographic projections using real empirical data.
Models land-use, perception, and biocultural interactions between two forager populations.
Biobehavioral interactions between two populations under different movement strategies.
Simulates biobehavioral interactions between 2 populations of hominins.
Displaying 10 of 20 results demography clear search