Computational Model Library

Our mission is to help computational modelers develop, document, and share their computational models in accordance with community standards and good open science and software engineering practices. Model authors can publish their model source code in the Computational Model Library with narrative documentation as well as metadata that supports open science and emerging norms that facilitate software citation, computational reproducibility / frictionless reuse, and interoperability. Model authors can also request private peer review of their computational models. Models that pass peer review receive a DOI once published.

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 feel free to contact us if you have any questions or concerns about publishing your model(s) in the Computational Model Library.

Displaying 10 of 194 results for "Sharon Greene" clear search

Informal Information Transmission Networks among Medieval Genoese Investors

Christopher Frantz | Published Wednesday, October 09, 2013 | Last modified Thursday, October 24, 2013

This model represents informal information transmission networks among medieval Genoese investors used to inform each other about cheating merchants they employed as part of long-distance trade operations.

Toward Market Structure as a Complex System: A Web Based Simulation Assignment Implemented in Netlogo

Timothy Kochanski | Published Monday, February 14, 2011 | Last modified Saturday, April 27, 2013

This is the model for a paper that is based on a simulation model, programmed in Netlogo, that demonstrates changes in market structure that occur as marginal costs, demand, and barriers to entry change. Students predict and observe market structure changes in terms of number of firms, market concentration, market price and quantity, and average marginal costs, profits, and markups across the market as firms innovate. By adjusting the demand growth and barriers to entry, students can […]

COOPER - Flood impacts over Cooperative Winemaking Systems

David Nortes Martinez David Nortes-Martinez | Published Thursday, February 08, 2018 | Last modified Friday, March 22, 2019

The model simulates flood damages and its propagation through a cooperative, productive, farming system, characterized as a star-type network, where all elements in the system are connected one to each other through a central element.

Spatial Game Theory

Kristin Crouse | Published Tuesday, November 05, 2019 | Last modified Wednesday, April 22, 2026

This model is a spatial evolutionary game theory model in which animals with inherited red or blue phenotypes move, interact locally, gain or lose energy based on payoff structure, and reproduce across generations. Plants provide a stationary green component of the environment. The model can be used to examine how game payoffs, inheritance, and survival shape population and evolutionary dynamics over time.

We present an agent-based model for the sharing economy, in the short-time accommodations market, where peers participating as suppliers and demanders follow simple decision rules about sharing market participation, according to their heterogeneous characteristics. We consider the sharing economy mainly as a peer-to-peer market where the access is preferred to ownership, excluding professional agents using sharing platforms as Airbnb to promote their business.

Informal risk-sharing cooperatives : ORP and Learning

Juliette Rouchier Victorien Barbet Renaud Bourlès | Published Monday, February 13, 2017 | Last modified Tuesday, May 16, 2023

The 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.

This model simulates a group of farmers that have encounters with individuals of a wildlife population. Each farmer owns a set of cells that represent their farm. Each farmer must decide what cells inside their farm will be used to produce an agricultural good that is self in an external market at a given price. The farmer must decide to protect the farm from potential encounters with individuals of the wildlife population. This decision in the model is called “fencing”. Each time that a cell is fenced, the chances of a wildlife individual to move to that cell is reduced. Each encounter reduces the productive outcome obtained of the affected cell. Farmers, therefore, can reduce the risk of encounters by exclusion. The decision of excluding wildlife is made considering the perception of risk of encounters. In the model, the perception of risk is subjective, as it depends on past encounters and on the perception of risk from other farmers in the community. The community of farmers passes information about this risk perception through a social network. The user (observer) of the model can control the importance of the social network on the individual perception of risk.

Peer reviewed Vigilant sharing in a small-scale society

Marcos Pinheiro | Published Wednesday, July 22, 2020 | Last modified Wednesday, July 29, 2020

The model explores food distribution patterns that emerge in a small-scale non-agricultural group when sharing individuals engage in intentional consumption leveling with a given probability.

In his 2003 book, Historical Dynamics (ch. 4), Turchin describes and briefly analyzes a spatial ABM of his metaethnic frontier theory, which is essentially a formalization of a theory by Ibn Khaldun in the 14th century. In the model, polities compete with neighboring polities and can absorb them into an empire. Groups possess “asabiya”, a measure of social solidarity and a sense of shared purpose. Regions that share borders with other groups will have increased asabiya do to salient us vs. them competition. High asabiya enhances the ability to grow, work together, and hence wage war on neighboring groups and assimilate them into an empire. The larger the frontier, the higher the empire’s asabiya.
As an empire expands, (1) increased access to resources drives further growth; (2) internal conflict decreases asabiya among those who live far from the frontier; and (3) expanded size of the frontier decreases ability to wage war along all frontiers. When an empire’s asabiya decreases too much, it collapses.  Another group with more compelling asabiya eventually helps establish a new empire.

The model represents migration of the green sea turtle, Chelonia mydas, between foraging and breeding sites in the Southwest Indian Ocean. The purpose of the model is to investigate the impact of local environmental conditions, including the quality of foraging sites and ocean currents, on emerging migratory corridors and reproductive output and to thereby identify conservation priority sites.

Corresponding article to found here: https://onlinelibrary.wiley.com/doi/epdf/10.1002/ece3.5552

Displaying 10 of 194 results for "Sharon Greene" clear search

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