Computational Model Library

Displaying 10 of 771 results for "Jon Solera" clear search

Landscape connectivity and predator–prey population dynamics

Jacopo A. Baggio | Published Thursday, November 10, 2011 | Last modified Saturday, April 27, 2013

A simple model to assess the effect of connectivity on interacting species (i.e. predator-prey type)

MCR Model

Davide Secchi Nuno R Barros De Oliveira | Published Friday, July 22, 2016 | Last modified Saturday, January 23, 2021

The aim of the model is to define when researcher’s assumptions of dependence or independence of cases in multiple case study research affect the results — hence, the understanding of these cases.

The Geography of Conflict Diamonds: The Case of Sierra Leone

Andrew Crooks Bianica Pires | Published Thursday, March 24, 2016 | Last modified Thursday, March 24, 2016

Using Sierra Leone as a test case, the purpose of the model is to explore the role of geography in a resource-driven war. An ABM is integrated with geographic information systems (GIS) for this purpose.

Simulation model for compliance behaviour

Esther Van Asselt Sjoukje A Osinga | Published Friday, October 03, 2014 | Last modified Tuesday, December 08, 2015

This model can be used to optimize intervention strategies for inspection services.

Cetina ABM

Maja Gori Frederik Schaff | Published Sunday, February 16, 2025

We provide a theory-grounded, socio-geographic agent-based model to present a possible explanation for human movement in the Adriatic region within the Cetina phenomenon.

Focusing on ideas of social capital theory from Piere Bordieu (1986), we implement agent mobility in an abstract geography based on cultural capital (prestige) and social capital (social position). Agents hold myopic representations of social (Schaff, 2016) and geographical networks and decide in a heuristic way on moving (and where) or staying.

The model is implemented in a fork of the Laboratory for Simulation Development (LSD), appended with GIS capabilities (Pereira et. al. 2020).

This is an agent-based model with two types of agents: customers and insurers. Insurers are price-takers who choose how much to spend on their service quality, and customers evaluate insurers based on premium, brand preference, and their perceived service quality. Customers are also connected in a small-world network and may share their opinions with their network.

The ABM contains two types of agents: insurers and customers. These act within the environment of a motor insurance market. At each simulation, the model undergoes the following steps:

  1. Network generation: At the start of the simulation, the model generates a small world network of social links between the customers, and randomly assigns each customer to an initial insurer
  2. ...

Disparities in access to primary health care have led to health disadvantages among Latinos and other non-White racial groups. To better identify and understand which policies are most likely to improve health care for Latinos, we examined differences in access to primary care between Latinos with proficient English language skills and Latinos with limited English proficiency (LEP) and estimated the extent of access to primary care providers (PCPs) among Latinos in the U.S.

Model to simulation the landscape of possible shedding games

Marco Janssen | Published Sunday, May 16, 2010 | Last modified Saturday, April 27, 2013

This model simulates 2048 versions of shedding games and evaluates the consequences on the average length and the difficulty of the game agents experience. The purpose of the model is to understand th

Friendship Games Rev 1.0

David Dixon | Published Friday, October 07, 2011 | Last modified Saturday, April 27, 2013

A friendship game is a kind of network game: a game theory model on a network. This is a NetLogo model of an agent-based adaptation of “‘Friendship-based’ Games” by PJ Lamberson. The agents reach an equilibrium that depends on the strategy played and the topology of the network.

Peer reviewed MOOvPOPsurveillance

Matthew Gompper Aniruddha Belsare Joshua J Millspaugh | Published Tuesday, April 04, 2017 | Last modified Tuesday, May 12, 2020

MOOvPOPsurveillance was developed as a tool for wildlife agencies to guide collection and analysis of disease surveillance data that relies on non-probabilistic methods like harvest-based sampling.

Displaying 10 of 771 results for "Jon Solera" clear search

This website uses cookies and Google Analytics to help us track user engagement and improve our site. If you'd like to know more information about what data we collect and why, please see our data privacy policy. If you continue to use this site, you consent to our use of cookies.
Accept