Computational Model Library

Displaying 10 of 145 results for "Reginald Lee Hayes" clear search

Diffusion of innovations

Marco Janssen | Published Tuesday, January 14, 2020

3 simple models to illustrate diffusion of innovations.
The models are discussed in Introduction to Agent-Based Modeling by Marco Janssen. For more information see https://intro2abm.com/

Forager mobility and interaction

L S Premo | Published Thursday, January 10, 2013 | Last modified Saturday, April 27, 2013

This is a relatively simple foraging-radius model, as described first by Robert Kelly, that allows one to quantify the effect of increased logistical mobility (as represented by increased effective foraging radius, r_e) on the likelihood that 2 randomly placed central place foragers will encounter one another within 5000 time steps.

Token Foraging in a Commons Dilemma

Nicholas Radtke | Published Monday, August 31, 2009 | Last modified Saturday, April 27, 2013

The model aims to mimic the observed behavior of participants in spatially explicit dynamic commons experiments.

The School Enrollment Model is a spatially-explicit computational model that depicts a city, with schools and students located within the space. The model represents the Chilean school system, a market-based educational system, where people are free to choose among public, private voucher, or private fee-paying schools. In the model, students become aware of some schools, apply to schools, switch schools, pass or fail grade levels, and eventually either graduate or dropout. Schools select students, update their tuition, test scores, and other characteristics.

The purpose of the model is to represent the Chilean school system and analyze the different mechanisms that affected the enrollment distribution between public, private voucher, and private fee-paying school sectors during the period 2004-2016.

Governing the commons

Marco Janssen | Published Tuesday, January 14, 2020 | Last modified Sunday, July 17, 2022

Model on the use of shared renewable resources including impact of imitation via success-bias and altruistic punishment.
The model is discussed in Introduction to Agent-Based Modeling by Marco Janssen. For more information see https://intro2abm.com/

Peer reviewed Artificial Anasazi

Marco Janssen | Published Tuesday, September 07, 2010 | Last modified Saturday, April 27, 2013

Replication of the well known Artificial Anasazi model that simulates the population dynamics between 800 and 1350 in the Long House Valley in Arizona.

Peer reviewed AZOI: Another Zone Of Influence model

Cyril Piou | Published Wednesday, July 23, 2014 | Last modified Thursday, December 11, 2014

This model reimplement Weiner et al. 2001 Zone Of Influence model to simulate plant growth under competition. The reimplementation in Netlogo and the ODD description in the “info” tab try to be as consistent as possible with the original paper.

Cluster Analysis

Lars Spång | Published Sunday, January 14, 2018

This model illustrates how to apply a simple cluster-analysis on points distributed around 5 centers. The result can be displayed in shades of a color or a spectacular colored pattern.

MERCURY extension: population

Tom Brughmans | Published Thursday, May 23, 2019

This model is an extended version of the original MERCURY model (https://www.comses.net/codebases/4347/releases/1.1.0/ ) . It allows for experiments to be performed in which empirically informed population sizes of sites are included, that allow for the scaling of the number of tableware traders with the population of settlements, and for hypothesised production centres of four tablewares to be used in experiments.

Experiments performed with this population extension and substantive interpretations derived from them are published in:

Hanson, J.W. & T. Brughmans. In press. Settlement scale and economic networks in the Roman Empire, in T. Brughmans & A.I. Wilson (ed.) Simulating Roman Economies. Theories, Methods and Computational Models. Oxford: Oxford University Press.

Individually parameterized mussels (Mytilus californianus) recruit, grow, move and die in a 3D environment while facing predation (in the form of seastar agents), heat and desiccation with increased tide height, and storms. Parameterized with data collected by Wootton, Paine, Kandur, Donahue, Robles and others. See my 2019 CoMSES video presentation to learn more.

Displaying 10 of 145 results for "Reginald Lee Hayes" clear search

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