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 4 of 14 results for "Jonatan Almagor" clear search
CA-MRSA Demonstration Model
Jonathan Ozik Charles Macal Kenneth Letendre Irene Lee | Published Tuesday, January 06, 2015We 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.
Last Mile Commuter Behavior Model
Moira Zellner Dean Massey Yoram Shiftan Jonathan Levine Maria Arquero | Published Friday, November 07, 2014 | Last modified Friday, November 07, 2014We represent commuters and their preferences for transportation cost, time and safety. Agents assess their options via their preferences, their environment, and the modes available. The model has policy levers to test impact on last-mile problem.
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.
Mobility, Ethnicity, and Language-Based Immigrant Settlement Model - MELBIS
Liliana Perez Suzana Dragicevic Taylor Anderson Jonathan Gaudreau Aaron Leung | Published Monday, June 14, 2021 | Last modified Monday, June 14, 2021MELBIS-V1 is a spatially explicit agent-based model that allows the geospatial simulation of the decision-making process of newcomers arriving in the bilingual cities and boroughs of the island of Montreal, Quebec in CANADA, and the resulting urban segregation spatial patterns. The model was implemented in NetLogo, using geospatial raster datasets of 120m spatial resolution.
MELBIS-V2 enhances MELBIS-V1 to implement and simulate the decision-making processes of incoming immigrants, and to analyze the resulting spatial patterns of segregation as immigrants arrive and settle in various cities in Canada. The arrival and segregation of immigrants is modeled with MELBIS-V2 and compared for three major Canadian immigration gateways, including the City of Toronto, Metro Vancouver, and the City of Calgary.
Displaying 4 of 14 results for "Jonatan Almagor" clear search