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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The AMMA simulates how news waves emerge in the mass media. Drawing on the ideas of public arena models and issue-attention cycles, it represents fundamental principles of public communication in a virtual media system.
Simulates impacts of ants killing colony mates when in conflict with another nest. The murder rate is adjustable, and the environmental change is variable. The colonies employ social learning so knowledge diffusion proceeds if interactions occur.
The purpose of this model is to enhance a basic ABM through a simple set of rules identified using the activity-driven models in order to produce more realistic patterns of pedestrian movement.
How natural population ageing affects UK household spending patterns.
This model aims to investigate how different type of learning (social system) and disturbance specific attributes (ecological system) influence adoption of treatment strategies to treat the effects of ecological disturbances.
This repository contains an agent-based simulation model exploring how status hierarchies influence the emergence and sustainability of cooperation in task-oriented groups. The model builds on evolutionary game theory to examine the dynamics of cooperation under single-leader and multi-leader hierarchies, investigating factors such as group size, assortativity, and hierarchical clarity. Key findings highlight the trade-offs between different leadership structures in fostering group cooperation and reveal the conditions under which cooperation is most stable.
The repository includes code for simulations, numerical analysis scripts, and visualization tools to replicate the results presented in the manuscript titled “Status hierarchies and the emergence of cooperation in task groups.”
Feel free to explore, reproduce the findings, or adapt the model for further research!
A simplified Arthur & Polak logic circuit model of combinatory technology build-out via incremental development. Only some inventions trigger radical effects, suggesting they depend on whole interdependent systems rather than specific innovations.
We model the relationship between natural resource userĀ“s individual time preferences and their use of destructive extraction method in the context of small-scale fisheries.
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).
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