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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The Weather model is a procedural generation model designed to create realistic daily weather data for socioecological simulations. It generates synthetic weather time series for solar radiation, temperature, and precipitation using algorithms based on sinusoidal and double logistic functions. The model incorporates stochastic variation to mimic unpredictable weather patterns and aims to provide realistic yet flexible weather inputs for exploring diverse climate scenarios.
The Weather model can be used independently or integrated into larger models, providing realistic weather patterns without extensive coding or data collection. It can be customized to meet specific requirements, enabling users to gain a better understanding of the underlying mechanisms and have greater confidence in their applications.
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The ForagerNet3_Demography model is a non-spatial ABM designed to serve as a platform for exploring several aspects of hunter-gatherer demography.
Violence against women occurs predominantly in the family and domestic context. The COVID-19 pandemic led Brazil to recommend and, at times, impose social distancing, with the partial closure of economic activities, schools, and restrictions on events and public services. Preliminary evidence shows that intense co- existence increases domestic violence, while social distancing measures may have prevented access to public services and networks, information, and help. We propose an agent-based model (ABM), called VIDA, to illustrate and examine multi-causal factors that influence events that generate violence. A central part of the model is the multi-causal stress indicator, created as a probability trigger of domestic violence occurring within the family environment. Two experimental design tests were performed: (a) absence or presence of the deterrence system of domestic violence against women and measures to increase social distancing. VIDA presents comparative results for metropolitan regions and neighbourhoods considered in the experiments. Results suggest that social distancing measures, particularly those encouraging staying at home, may have increased domestic violence against women by about 10%. VIDA suggests further that more populated areas have comparatively fewer cases per hundred thousand women than less populous capitals or rural areas of urban concentrations. This paper contributes to the literature by formalising, to the best of our knowledge, the first model of domestic violence through agent-based modelling, using empirical detailed socioeconomic, demographic, educational, gender, and race data at the intraurban level (census sectors).
(An empty output folder named “NETLOGOexperiment” in the same location with the LAKEOBS_MIX.nlogo file is required before the model can be run properly)
The model is motivated by regime shifts (i.e. abrupt and persistent transition) revealed in the previous paleoecological study of Taibai Lake. The aim of this model is to improve a general understanding of the mechanism of emergent nonlinear shifts in complex systems. Prelimnary calibration and validation is done against survey data in MLYB lakes. Dynamic population changes of function groups can be simulated and observed on the Netlogo interface.
Main functional groups in lake ecosystems were modelled as super-individuals in a space where they interact with each other. They are phytoplankton, zooplankton, submerged macrophyte, planktivorous fish, herbivorous fish and piscivorous fish. The relationships between these functional groups include predation (e.g. zooplankton-phytoplankton), competition (phytoplankton-macrophyte) and protection (macrophyte-zooplankton). Each individual has properties in size, mass, energy, and age as physiological variables and reproduce or die according to predefined criteria. A system dynamic model was integrated to simulate external drivers.
Set biological and environmental parameters using the green sliders first. If the data of simulation are to be logged, set “Logdata” as true and input the name of the file you want the spreadsheet(.csv) to be called. You will need create an empty folder called “NETLOGOexperiment” in the same level and location with the LAKEOBS_MIX.nlogo file. Press “setup” to initialise the system and “go” to start life cycles.
The model integrates major theories of political judgment and behavior within the classical cognitive paradigm embedded in the ACT-R cognitive architecture. It models preferences and beliefs of political candidates, parties, and groups.
We used our model to test how different combinations of dominance interactions present in H. saltator could result in linear, despotic, or shared hierarchies.
The model implements a double auction financial markets with two types of agents: rational and noise. The model aims to study the impact of different compensation structure on the market stability and market quantities as prices, volumes, spreads.
This model examines the potential impact of market collapse on the economy and demography of fishing households in the Logone Floodplain, Cameroon.
This model makes it possible to explore how network clustering and resistance to changing existing status beliefs might affect the spontaneous emergence and diffusion of such beliefs as described by status construction theory.
This model was built to estimate the impacts of exogenous fodder input and credit loans services on livelihood, rangeland health and profits of pastoral production in a small holder pastoral household in the arid steppe rangeland of Inner Mongolia, China. The model simulated the long-term dynamic of herd size and structure, the forage demand and supply, the cash flow, and the situation of loan debt under three different stocking strategies: (1) No external fodder input, (2) fodders were only imported when natural disaster occurred, and (3) frequent import of external fodder, with different amount of available credit loans. Monte-Carlo method was used to address the influence of climate variability.
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