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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This model simulates how collective self-organisation among individuals that manage irrigation resource collectively.
This model simulates how the strategy one manages time affect the well-being that he/she can obtain.
We build a computational model to investigate, in an evolutionary setting, a series of questions pertaining to happiness.
FlowLogo integrates agent-based and groundwater flow simulation. It aims to simplify the process of developing participatory ABMs in the groundwater space and begin the exploration of novel, bottom-up solutions to conflicts in shared aquifers.
Simulates the construction of scientific journal publications, including authors, references, contents and peer review. Also simulates collective learning on a fitness landscape. Described in: Watts, Christopher & Nigel Gilbert (forthcoming) “Does cumulative advantage affect collective learning in science? An agent-based simulation”, Scientometrics.
The model explores the emergence of inequality in cognitive and socio-emotional skills at the societal level within and across generations that results from differences in parental investment behavior during childhood and adolescence.
This simulation model is to simulate the emergence of technological innovation processes from the hypercycles perspective.
This is a complex “Data Integration Model”, following a “KIDS” rather than a “KISS” methodology - guided by the available evidence. It looks at the complex mix of social processes that may determine why people vote or not.
We explore how dynamic processes related to socioeconomic inequality operate to sort students into, and create stratification among, colleges.
This is a multi-patch meta-population ecological model. It intended as a test-bed in which to test the impact of humans with different kinds of social structure.
Displaying 10 of 70 results agent-based simulation clear search