About the CoMSES Model Library more info
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.
Displaying 3 of 3 results for 'Jose Jimenez'
Proof of principle for a self-governing prediction and forecasting reward algorithm: Modeling consensus of a group of experts in adversarial collaboration.
Jose Osvaldo Gonzalez Hernandez Jonathan Marino Ted C. Rogers Brandon Velasco | Published Sunday, May 14, 2023Package for simulating the behavior of experts in a scientific-forecasting competition, where the outcome of experiments itself depends on expert consensus. We pay special attention to the interplay between expert bias and trust in the reward algorithm. The package allows the user to reproduce results presented in arXiv:2305.04814, as well as testing of other different scenarios.
Knowledge Sharing in a Hospital
bpint Emily Molfino Joshua Goldstein Kathryn Schaefer Ziemer Mark Orr Bryan Lewis Jose Jimenez | Published Friday, January 27, 2023Organizations are complex systems comprised of many dynamic and evolving interaction patterns among individuals and groups. Understanding these interactions and how patterns, such as informal structures and knowledge sharing behavior, emerge are crucial to creating effective and efficient organizations. To explore such organizational dynamics, the agent-based model integrates a cognitive model, dynamic social networks, and a physical environment.
Gunpowder battle tactics
Xavier Rubio-Campillo Jose María Cela Francesc Xavier Hernàndez | Published Wednesday, November 20, 2013 | Last modified Tuesday, November 26, 2013This model simulates the dynamics of eighteenth-century infantry battle tactics. The goal is to explore the effect of different tactics and individual traits in the dynamics of the combat.