Computational Model Library

Displaying 10 of 351 results for "John C Moore" clear search

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).

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.

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 […]

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.

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.

The Groundwater Commons Game

Juan Castilla-Rho Rodrigo Rojas | Published Thursday, May 11, 2017 | Last modified Saturday, September 16, 2017

The Groundwater Commons Game synthesises and extends existing work on human cooperation and collective action, to elucidate possible determinants and pathways to regulatory compliance in groundwater systems globally.

The purpose of the simulation was to explore and better understand the process of bridging between an analysis of qualitative data and the specification of a simulation. This may be developed for more serious processes later but at the moment it is merely an illustration.
This exercise was done by Stephanie Dornschneider (School of Politics and International Relations, University College Dublin) and Bruce Edmonds to inform the discussion at the Lorentz workshop on “Integrating Qualitative and Quantitative Data using Social Simulation” at Leiden in April 2019. The qualitative data was collected and analysed by SD. The model specification was developed as the result of discussion by BE & SD. The model was programmed by BE. This is described in a paper submitted to Social Simulation 2019 and (to some extent) in the slides presented at the workshop.

Displaying 10 of 351 results for "John C Moore" clear search

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