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.

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Modeling information Asymmetries in Tourism

Jacopo A. Baggio Rodolfo Baggio | Published Monday, January 09, 2012 | Last modified Saturday, April 27, 2013

A very simple model elaborated to explore what may happens when buyers (travelers) have more information than sellers (tourist destinations)

9 Maturity levels in Empirical Validation - An innovation diffusion example

Martin Rixin | Published Wednesday, October 19, 2011 | Last modified Saturday, April 27, 2013

Several taxonomies for empirical validation have been published. Our model integrates different methods to calibrate an innovation diffusion model, ranging from simple randomized input validation to complex calibration with the use of microdata.

Hominin ecodynamics v.2

C Michael Barton | Published Monday, September 19, 2011 | Last modified Friday, March 28, 2014

Simulates biobehavioral interactions between 2 populations of hominins.

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.

ABODE - Agent Based Model of Origin Destination Estimation

D Levinson | Published Monday, August 29, 2011 | Last modified Saturday, April 27, 2013

The agent based model matches origins and destinations using employment search methods at the individual level.

Objective is to simulate policy interventions in an integrated demand-supply model. The underlying demand function links both sides. Diffusion proceeds if interactions distribute awareness (Epidemic effect) and rivalry reduces the market price (Probit effect). Endogeneity is given due to the fact that consumer awareness as well as their willingness-to-pay drives supply-side rivalry. Firm´s entry and exit decisions as well as quantity and price settings are driven by Cournot competition.

A consumer-demand simulation for Smart Metering tariffs (Innovation Diffusion)

Martin Rixin | Published Thursday, August 18, 2011 | Last modified Saturday, April 27, 2013

An Agent-based model simulates consumer demand for Smart Metering tariffs. It utilizes the Bass Diffusion Model and Rogers´s adopter categories. Integration of empirical census microdata enables a validated socio-economic background for each consumer.

Nudging agents in social networks for collective action

Marco Janssen | Published Sunday, August 14, 2011 | Last modified Sunday, March 17, 2019

Agents are linked in a social-network and make decisions on which of 2 types of behavior to adopt. We explore consequences of different information feedback and providing targeted feedback to individuals.

CRESY-II

Cara Kahl | Published Friday, July 08, 2011 | Last modified Monday, August 04, 2014

CREativity from a SYstems perspective, Model II.

CRESY-I

Cara Kahl | Published Friday, July 08, 2011 | Last modified Saturday, April 27, 2013

CRESY-I stands for CREativity from a SYstems perspetive, Model I. This is the base model in a series designed to describe a systems approach to creativity in terms of variation, selection and retention (VSR) subprocesses.

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