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 4 results for 'Douglas%20Wright'

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, 2021

The 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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An Agent-Based Model of Insurance Customer Behaviour with Word of Mouth Network in C#

Rei England Iqbal Owadally Douglas Wright | Published Friday, March 04, 2022

This is an agent-based model with two types of agents: customers and insurers. Insurers are price-takers who choose how much to spend on their service quality, and customers evaluate insurers based on premium, brand preference, and their perceived service quality. Customers are also connected in a small-world network and may share their opinions with their network.

The ABM contains two types of agents: insurers and customers. These act within the environment of a motor insurance market. At each simulation, the model undergoes the following steps:

Network generation: At the start of the simulation, the model generates a small world network of social links between the customers, and randomly assigns each customer to an initial insurer

Agent-based model of WiFi tracking system in urban environment

Christopher Thron Khoi Tran | Published Friday, April 21, 2017

This code simulates the WiFi user tracking system described in: Thron et al., “Design and Simulation of Sensor Networks for Tracking Wifi Users in Outdoor Urban Environments”. Testbenches used to create the figures in the paper are included.

From Schelling to Schools

V Stoica A Flache | Published Sunday, June 23, 2013

We propose here a computational model of school segregation that is aligned with a corresponding Schelling-type model of residential segregation. To adapt the model for application to school segregation, we move beyond previous work by combining two preference arguments in modeling parents’ school choice, preferences for the ethnic composition of a school and preferences for minimizing the travelling distance to the school.