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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In this Repast model the ‘Consumat’ cognitive framework is applied to an ABM of the Dutch car market. Different policy scenarios can be selected or created to examine their effect on the diffusion of EVs.
AMBAWA simulates the flows of biomass between crop and livestock systems at the field, farm, and village scales in order to showcase innovating management practices of soil fertility in West Africa.
This model (CharRec) creates simulated charcoal records, based on differing natural and anthropogenic patterns of ignitions, charcoal dispersion, and deposition.
The program simulate the functioning of an italian health and social public information office (SPUN) on the basis of the real data collected in the first five years of functioning.
This model is to match students and schools using real-world student admission mechanisms. The mechanisms in this model are serial dictatorship, deferred acceptance, the Boston mechanism, Chinese Parallel, and the Taipei mechanism.
A multithreaded replication of the PPHPC model in Java for testing different ABM parallelization strategies.
We developed an agent-based model to explore underlying mechanisms of behavioral clustering that we observed in human online shopping experiments.
Agents can influence each other if they are close enough in knowledge. The probability to convince with good knowledge and number of agents have an impact on the dissemination of knowledge.
This model simulates the emergence of a dual market structure from firm-level interaction. Firms are profit-seeking, and demand is represented by a unimodal distribution of consumers along a set of taste positions.
This model builds on inquisitiveness as a key individual disposition to expand the bounds of their rationality. It represents a system where teams are formed around problems and inquisitive agents integrate competencies to find ‘emergent’ solutions.
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