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 26 results reproduction clear search
Fertility Tradeoffs is an agent-based model that examines how parental investment strategies evolve under density-dependent conditions. Humans occupy territories that compete for limited space, and reproduction requires both resources and available territory. Individuals inherit investment strategies that determine how much time and resources are required to raise a child, creating a tradeoff between number of children and investment per child. As space fills, territory costs increase and population growth slows, producing logistic-like dynamics. By manipulating child mortality and resource availability, the model demonstrates how environmental conditions shape both population outcomes and the evolution of reproductive strategies.
This is a modification of a model published previous by Barton and Riel-Salvatore (2012). In this model, we simulate six regional populations within Last Glacial Maximum western Europe. Agents interact through reproduction and genetic markers attached to each of six regions mix through subsequent generations as a way to track population dynamics, mobility, and gene flow. In addition, the landscape is heterogeneous and affects agent mobility and, under certain scenarios, their odds of survival.
RAGE models a stylized common property grazing system. Agents follow a certain behavioral type. The model allows analyzing how household behavior with respect to a social norm on pasture resting affects long-term social-ecological system dynamics.
PSoup is an educational program in which evolution is demonstrated, on the desk-top, as you watch. Blind bugs evolve sophisticated heuristic search algorithms to be the best at finding food fast.
The ForagerNet3_Demography model is a non-spatial ABM designed to serve as a platform for exploring several aspects of hunter-gatherer demography.
Evolution of Sex is a NetLogo model that illustrates the advantages and disadvantages of sexual and asexual reproductive strategies. It seeks to demonstrate the answer to the question “Why do we have sex?”
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.
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 natural selection of foresight, an accuracy at assess the environment, under degrees of environmental heterogeneity. The model is designed to connect local scale mobility, from foraging, with the global scale phenomenon of population dispersal.
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.
Displaying 10 of 26 results reproduction clear search