Computational Model Library

Displaying 10 of 1138 results for "Ian M Hamilton" clear search

Institutional change

Abigail Sullivan | Published Friday, October 07, 2016 | Last modified Sunday, December 02, 2018

This model builds on another model in this library (“diffusion of culture”).

Hohokam Water Management Simulation (HWM)

John Murphy | Published Wednesday, August 31, 2011 | Last modified Saturday, April 27, 2013

Simulation of irrigation system management using archaeological data from southern Arizona

Absorption of particulate matter by leafs

Georg Jäger Chiara Letter | Published Monday, November 12, 2018 | Last modified Monday, November 12, 2018

This model aims to understand the interaction between particulate matter and leaves of trees. The particles collide with the leaf and can either be absorbed with a certain probability, otherwise they bounce off it. The absorptions are detected in a counter.
The movement of the particles depends mainly on the strength and direction of the wind and the air temperature. They also show a certain random movement, but the proportion is negligible.
In a collision with the leaf, the particles are absorbed with a certain probability (absorption-probability), otherwise repelled.

Zombies

Jennifer Badham | Published Tuesday, June 08, 2021

Zombies move toward humans and humans move (faster) away from zombies. They fight if they meet, and humans who lose become zombies.

Setting the Stage for Inequality

Timothy Dennehy | Published Monday, March 11, 2013 | Last modified Saturday, April 27, 2013

How can a strictly egalitarian social system give way to a stratified society if all of its members punish each other for any type of selfish behavior? This model examines the role of prestige bias in constant and variable environments on the development of hierarchies of wealth.

Pastoralscape

Matthew Sottile | Published Tuesday, October 12, 2021

Pastoralscape is a model of human agents, lifestock health and contageous disease for studying the impact of human decision making in pastoral communities within East Africa on livestock populations. It implements an event-driven agent based model in Python 3.

IOP 2.1.2 is an agent-based simulation model designed to explore the relations between (1) employees, (2) tasks and (3) resources in an organizational setting. By comparing alternative cognitive strategies in the use of resources, employees face increasingly demanding waves of tasks that derive by challenges the organization face to adapt to a turbulent environment. The assumption tested by this model is that a successful organizational adaptation, called plastic, is necessarily tied to how employees handle pressure coming from existing and new tasks. By comparing alternative cognitive strategies, connected to ‘docility’ (Simon, 1993; Secchi, 2011) and ‘extended’ cognition (Clark, 2003, Secchi & Cowley, 2018), IOP 2.1.2 is an attempt to indicate which strategy is most suitable and under which scenario.

Group assortment with preference rankings

Fredrik Jansson | Published Thursday, July 14, 2016 | Last modified Monday, April 09, 2018

This model uses preference rankings w.r.t. ethnic group compositions (e.g. at companies) and assigns ethnic agents to groups based on their rankings.

The model simulates the spread of a virus through a synthetic network with a degree distribution calibrated on close-range contact data. The model is used to study the macroscopic consequences of cross-individual variability in close-range contact frequencies and to assess whether this variability can be exploited for effective intervention targeting high-contact nodes.

The model is an experimental ground to study the impact of network structure on diffusion. It allows to construct a social network that already has some measurable level of homophily, and simulate a diffusion process over this social network.

Displaying 10 of 1138 results for "Ian M Hamilton" clear search

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