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.
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Adaptive model of a consumer advice network
Peng Shao | Published Monday, May 14, 2018In the consumer advice network, users with connections can interact with each other, and the network topology will change during the opinion interaction. When the opinion distance from i to j is greater than the confidence threshold, the two consumers cannot exchange opinions, and the link between them will disconnect with probability DE. Then, a link from node i to node k is established with probability CE and node i learning opinion from node k.
Machine Learning simulates Agent-based Model
Bernardo Furtado | Published Wednesday, March 07, 2018This is an initial exploratory exercise done for the class @ http://thiagomarzagao.com/teaching/ipea/ Text available here: https://arxiv.org/abs/1712.04429v1
The program:
Reads output from an ABM model and its parameters’ configuration
Creates a socioeconomic optimal output based on two ABM results of the modelers choice
Organizes the data as X and Y matrices
Trains some Machine Learning algorithms
…
PercolationPrice
Koen Frenken Luis Izquierdo Paolo Zeppini | Published Thursday, December 21, 2017 | Last modified Thursday, May 03, 2018This model simulate product diffusion on different social network structures.
Dynamic pricing strategies for perishable products in a competitive multi-agent retailer market
Wenchong Chen Hongwei Liu | Published Monday, November 27, 2017 | Last modified Thursday, March 01, 2018This model explores a price Q-learning mechanism for perishable products that considers uncertain demand and customer preferences in a competitive multi-agent retailer market (a model-free environment).
The Informational Dynamics of Regime Change
Dominik Klein Johannes Marx | Published Saturday, October 07, 2017 | Last modified Tuesday, January 14, 2020We model the epistemic dynamics preceding political uprising. Before deciding whether to start protests, agents need to estimate the amount of discontent with the regime. This model simulates the dynamics of group knowledge about general discontent.
Success bias imitation increases the probability of effectively dealing with ecological disturbances
Jacopo A. Baggio Vicken Hillis | Published Thursday, April 13, 2017 | Last modified Thursday, August 02, 2018This model aims to investigate how different type of learning (social system) and disturbance specific attributes (ecological system) influence adoption of treatment strategies to treat the effects of ecological disturbances.
LBD Model: Learning-by-doing for sustainable management of renewable resources
Emilie Lindkvist Örjan Ekeberg Jon Norberg | Published Thursday, March 09, 2017This is a simulation model of an intelligent agent that has the objective to learn sustainable management of a renewable resource, such as a fish stock.
Managing ecological disturbances: Learning and the structure of social-ecological networks
Jacopo A. Baggio Vicken Hillis | Published Friday, March 03, 2017 | Last modified Thursday, August 02, 2018The aim of this model is to explore and understand the factors driving adoption of treatment strategies for ecological disturbances, considering payoff signals, learning strategies and social-ecological network structure
Informal risk-sharing cooperatives : ORP and Learning
Juliette Rouchier Victorien Barbet Renaud Bourlès | Published Monday, February 13, 2017 | Last modified Tuesday, May 16, 2023The model studies the dynamics of risk-sharing cooperatives among heterogeneous farmers. Based on their knowledge on their risk exposure and the performance of the cooperative farmers choose whether or not to remain in the risk-sharing agreement.
Institutional change
Abigail Sullivan | Published Friday, October 07, 2016 | Last modified Sunday, December 02, 2018This model builds on another model in this library (“diffusion of culture”).
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