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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A multithreaded replication of the PPHPC model in Java for testing different ABM parallelization strategies.
This model can be used to optimize intervention strategies for inspection services.
This model describes and analyses the Travel-Tour Case study.
chitwanabm is a spatially explicit agent-based model of population and land use in the Chitwan Valley, Nepal, designed to explore feedbacks between population and environment, with a heavy focus on community context and individual-level variation.
We present an agent-based model that maps out and simulates the processes by which individuals within ecological restoration organizations communicate and collectively make restoration decisions.
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.
Agents co-operate or defect towards other agents in a prisoner’s dilemma, with strategy choice depending on whether agents share tags or are kin in different social structures.
Indirect reciprocity can be evolved by the shared information among the people of small subgroups in the population.
This model illustrates a positive ‘growth’ feedback loop in which the areal extent of an entity increases through time.
This ABM deals with commuting choices in the Italian city of Varese. Empirical data inform agents’ attitudes and modal choices costs and emissions. We evaluate ex ante the impact of policies for less polluting commuting choices.
Displaying 10 of 1176 results