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 362 results for "John C Moore" clear search

Walk This Way

Crooks Andrew Sarah Wise | Published Thursday, August 27, 2015

The purpose of this model is to enhance a basic ABM through a simple set of rules identified using the activity-driven models in order to produce more realistic patterns of pedestrian movement.

This 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.

Feedback Loop Example: Wildland Fire Spread

James Millington | Published Friday, December 21, 2012 | Last modified Saturday, April 27, 2013

This model is a replication of that described by Peterson (2002) and illustrates the ‘spread’ feedback loop type described in Millington (2013).

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 […]

Hierarchy and War

Alan van Beek Michael Z. Lopate | Published Thursday, April 06, 2023

Scholars have written extensively about hierarchical international order, on the one hand, and war on the other, but surprisingly little work systematically explores the connection between the two. This disconnect is all the more striking given that empirical studies have found a strong relationship between the two. We provide a generative computational network model that explains hierarchy and war as two elements of a larger recursive process: The threat of war drives the formation of hierarchy, which in turn shapes states’ incentives for war. Grounded in canonical theories of hierarchy and war, the model explains an array of known regularities about hierarchical order and conflict. Surprisingly, we also find that many traditional results of the IR literature—including institutional persistence, balancing behavior, and systemic self-regulation—emerge from the interplay between hierarchy and war.

Evolution of Conditional Cooperation

M Manning Marco Janssen Oyita Udiani | Published Thursday, August 01, 2013 | Last modified Friday, May 13, 2022

Cultural group selection model used to evaluate the conditions for agents to evolve who have other-regarding preferences in making decisions in public good games.

We model the relationship between natural resource user´s individual time preferences and their use of destructive extraction method in the context of small-scale fisheries.

Peer reviewed Least cost path mobility

Colin Wren Claudine Gravel-Miguel | Published Saturday, September 02, 2017 | Last modified Monday, October 04, 2021

This model aims to mimic human movement on a realistic topographical surface. The agent does not have a perfect knowledge of the whole surface, but rather evaluates the best path locally, at each step, thus mimicking imperfect human behavior.

This model simulates the propagation of photons in a water tank. A source of light emits an impulse of photons with equal energy represented by yellow dots. These photons are then scattered by water particles before possibly reaching the photo-detector represented by a gray line. Different types of water are considered. For each one of them we calculate the total received energy.

The water tank is represented by a blue rectangle with fixed dimensions. It’s exposed to the air interface and has totally absorbent barriers. Four types of water are supported. Each one is characterized by its absorption and scattering coefficients.
At the source, the photons are generated uniformly with a random direction within the beamwidth. Each photon travels a random distance drawn from a distribution depending on the water characteristics before encountering a water particle.
Based on the updated position of the photon, three situations may occur:
-The photon hits the barrier of the tank on its trajectory. In this case it’s considered as lost since the barriers are assumed totally absorbent.

Sahelian transhumance is a seasonal pastoral mobility between the transhumant’s terroir of origin and one or more host terroirs. Sahelian transhumance can last several months and extend over hundreds of kilometers. Its purpose is to ensure efficient and inexpensive feeding of the herd’s ruminants. This paper describes an agent-based model to determine the spatio-temporal distribution of Sahelian transhumant herds and their impact on vegetation. Three scenarios based on different values of rainfall and the proportion of vegetation that can be grazed by transhumant herds are simulated. The results of the simulations show that the impact of Sahelian transhumant herds on vegetation is not significant and that rainfall does not impact the alley phase of transhumance. The beginning of the rainy season has a strong temporal impact on the spatial distribution of transhumant herds during the return phase of transhumance.

Displaying 10 of 362 results for "John C Moore" clear search

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