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 Jupyter Notebook clear search
Peer reviewed Dynamic Equilibria Prediction: Experience-Weighted Attraction (EWA), Python Implementation
Vinicius Ferraz | Published Friday, December 02, 2022This project is based on a Jupyter Notebook that describes the stepwise implementation of the EWA model in bi-matrix ( 2×2 ) strategic-form games for the simulation of economic learning processes. The output is a dataset with the simulated values of Attractions, Experience, selected strategies, and payoffs gained for the desired number of rounds and periods. The notebook also includes exploratory data analysis over the simulated output based on equilibrium, strategy frequencies, and payoffs.
3D Urban Traffic Simulator (ABM) in Unity
Sedar Olmez Obi Thompson Sargoni Alison Heppenstall Daniel Birks Annabel Whipp Ed Manley | Published Friday, January 22, 2021 | Last modified Monday, March 22, 2021The Urban Traffic Simulator is an agent-based model developed in the Unity platform. The model allows the user to simulate several autonomous vehicles (AVs) and tune granular parameters such as vehicle downforce, adherence to speed limits, top speed in mph and mass. The model allows researchers to tune these parameters, run the simulator for a given period and export data from the model for analysis (an example is provided in Jupyter Notebook).
The data the model is currently able to output are the following:
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Urban/Rural Adaptive Culture Model
Nick LaBerge | Published Sunday, July 19, 2020Contains python3 code used to replicate the culture model from the JASSS submission: “Modeling Cultural Dissemination and Divergence between Rural and Urban Regions.”