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 994 results for "Dave van Wees" clear search

An agent-based model to study the effects of trust in coalition formation

Luis Gustavo Nardin | Published Wednesday, August 31, 2011 | Last modified Saturday, April 27, 2013

This model is an agent-based simulation that consists of agents who play the spatial prisioner’s dilemma game with coalition formation. The coalition dynamics are mainly influenced by how much the agents trust their leaders. The main objective is provide a simulation model to enable the analysis of the impacts that the use of trust may cause in coalition formation.

An Agent-Based Model of Internet Diffusion Under General and Specific Network Externalities

Filiz Garip | Published Friday, April 27, 2012 | Last modified Saturday, April 27, 2013

Using nodes from the 2002 General Social Survey sample, the code establishes a network of ties with a given homophily bias, and simulates Internet adoption rates in that network under three conditions: (i) no network externalities, (ii) general network externalities, where an individual’s reservation price is a function of the overall adoption rate in the network, (iii) specific network externalities, where reservation price is a function of the adoption rate in individual’s personal […]

Aspiration, Attainment and Success: An agent-based model of distance-based school allocation

James Millington | Published Friday, November 02, 2012 | Last modified Friday, July 03, 2015

The purpose of this model is to investigate mechanisms driving the geography of educational inequality and the consequences of these mechanisms for individuals with varying attributes and mobility.

This agent-based model explores the existence of positive feedback loops related to illegal, unregulated, unreported (IUU) fishing; the use of forced labor; and the depletion of fish populations due to commercial fishing.

An agent based simple economy model that examines the effect of taxation and almsgiving (particularly Islamic almsgiving - zakat) for ameliorating wealth inequality.

This model is developed as a theoretical agent-based model to study the general phenomena of network-based targeting strategies on eco-innovation adoption and diffusion through inter-firm networks.

FLOSSSim: An Agent-Based Model of the Free/Libre Open Source Software (FLOSS) Development Process

Nicholas Radtke | Published Saturday, December 31, 2011 | Last modified Saturday, April 27, 2013

An agent-based model of the Free/Libre Open Source Software (FLOSS) development process designed around agents selecting FLOSS projects to contribute to and/or download.

Linear Threshold

Kaushik Sarkar | Published Saturday, November 03, 2012 | Last modified Saturday, April 27, 2013

NetLogo implementation of Linear Threshold model of influence propagation.

Positive feedback can lead to “trapping” in local optima. Adding a simple negative feedback effect, based on ant behaviour, prevents this trapping

This model aims to explore how gambling-like behavior can emerge in loot box spending within gaming communities. A loot box is a purchasable mystery box that randomly awards the player a series of in-game items. Since the contents of the box are largely up to chance, many players can fall into a compulsion loop of purchasing, as the fear of missing out and belief in the gambler’s fallacy allow one to rationalize repeated purchases, especially when one compares their own luck to others. To simulate this behavior, this model generates players in different network structures to observe how factors such as network connectivity, a player’s internal decision making strategy, or even common manipulations games use these days may influence a player’s transactions.

Displaying 10 of 994 results for "Dave van Wees" clear search

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