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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Model that illustrates the use of the GAMA advanced driving skill through a case study concerning the evacuation of the city of Rouen (France).
The computer model simulates the development of a social network (i.e. formation of friendships and cliques), the (dyadic) interactions between pupils and the development of similarities and differences in their behavioral profiles.
A multi-agent model of oligarchy in a spatial election simulation.
An agent-based model is used to simulate legislators’ behavior under secret voting rules, as influenced by the power of the accused politician, the composition of the voting body, and the publicity of the accusations.
We built an agent-based model to foster the understanding of homeowners’ insulation activity.
This model simulates a bank - firm credit network.
Model for the simulation of the Kiss Nightclub fevacuations with agents featring cognition, emotions, emotonal contagion, personality, social relations and norms.
Previous work with the spatial iterated prisoner’s dilemma has shown that “walk away” cooperators are able to outcompete defectors as well as cooperators that do not respond to defection, but it remains to be seen just how robust the so-called walk away strategy is to ecologically important variables such as population density, error, and offspring dispersal. Our simulation experiments identify socio-ecological conditions in which natural selection favors strategies that emphasize forgiveness over flight in the spatial iterated prisoner’s dilemma. Our interesting results are best explained by considering how population density, error, and offspring dispersal affect the opportunity cost associated with walking away from an error-prone partner.
To our knowledge, this is the first agent-based simulation of continuous-time PGGs (where participants can change contributions at any time) which are much harder to realise within both laboratory and simulation environments.
Work related to this simulation has been published in the following journal article:
Vu, Tuong Manh, Wagner, Christian and Siebers, Peer-Olaf (2019) ‘ABOOMS: Overcoming the Hurdles of Continuous-Time Public Goods Games with a Simulation-Based Approach’ Journal of Artificial Societies and Social Simulation 22 (2) 7 http://jasss.soc.surrey.ac.uk/22/2/7.html. doi: 10.18564/jasss.3995
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This Bicycle encounter model builds on the Salzburg Bicycle model (Wallentin & Loidl, 2015). It simulates cyclist flows and encounters, which are locations of potential accidents between cyclists.
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