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 purpose of the model is to explore the impacts of global change on the ability of a community of farmers to adapt their practices to an agricultural pest.
An algorithm implemented in NetLogo that can be used for searching resources.
We demonstrate how a simple model of community associated Methicillin-resistant Staphylococcus aureus (CA-MRSA) can be easily constructed by leveraging the statecharts and ReLogo capabilities in Repast Simphony.
Continuing on from the Adder model, this adaptation explores how rationality, learning and uncertainty influence the exploration of complex landscapes representing technological evolution.
A thermostat is a device that allows to have the temperature in a room near a desire value.
Complete Library for object oriented development of Classifier Systems. See for the concept behind.
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.
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.
Comparing 7 alternative models of human behavior and assess their performance on a high resolution dataset based on individual behavior performance in laboratory experiments.
This model is an extended version of the matching problem including the mate search problem, which is the generalization of a traditional optimization problem. The matching problem is extended to a form of asymmetric two-sided matching problem.
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