Computational Model Library

Displaying 10 of 942 results for "Jan Buurma" clear search

This model simulates the spread of anti-vaccine sentiments in cyber and physical space and how it creates emergence of clusters of anti-vacciners, which eventually lead to higher probablity of disease outbreaks.

This model explores a price Q-learning mechanism for perishable products that considers uncertain demand and customer preferences in a competitive multi-agent retailer market (a model-free environment).

Peer reviewed Agent-based Renewables model for Integrated Sustainable Energy (ARISE)

Anthony Halog Muhammad Indra Al Irsyad Rabindra Nepal | Published Wednesday, November 29, 2017 | Last modified Friday, October 05, 2018

ARISE is a hybrid energy model incorporating macroeconomic data, micro socio-economic data, engineering data and environmental data. This version of ARISE can simulate scenarios of solar energy policy for Indonesia case.

The model aims at estimating household energy consumption and the related greenhouse gas (GHG) emissions reduction based on the behavior of the individual household under different operationalizations of the Theory of Planned Behaviour (TPB).
The original model is developed as a tool to explore households decisions regarding solar panel investments and cumulative consequences of these individual choices (i.e. diffusion of PVs, regional emissions savings, monetary savings). We extend the model to explore a methodological question regarding an interpretation of qualitative concepts from social science theories, specifically Theory of Planned Behaviour in a formal code of quantitative agent-based models (ABMs). We develop 3 versions of the model: one TPB-based ABM designed by the authors and two alternatives inspired by the TPB-ABM of Schwarz and Ernst (2009) and the TPB-ABM of Rai and Robinson (2015). The model is implemented in NetLogo.

Human mate choice is a complex system

Paul Smaldino Jeffrey C Schank | Published Friday, February 08, 2013 | Last modified Saturday, April 27, 2013

A general model of human mate choice in which agents are localized in space, interact with close neighbors, and tend to range either near or far. At the individual level, our model uses two oft-used but incompletely understood decision rules: one based on preferences for similar partners, the other for maximally attractive partners.

ForagerNet3_Demography: A Non-Spatial Model of Hunter-Gatherer Demography

Andrew White | Published Thursday, October 17, 2013 | Last modified Thursday, October 17, 2013

ForagerNet3_Demography is a non-spatial ABM for exploring hunter-gatherer demography. Key methods represent birth, death, and marriage. The dependency ratio is an imporant variable in many economic decisions embedded in the methods.

ForagerNet3_Demography_V2

Andrew White | Published Thursday, February 13, 2014

ForagerNet3_Demography_V2 is a non-spatial ABM for exploring hunter-gatherer demography. This version (developed from FN3D_V1) contains code for calculating the ratio of old to young adults (the “OY ratio”) in the living and dead populations.

Agent-based model of sexual partnership

Andrea Knittel | Published Monday, December 05, 2011 | Last modified Saturday, April 27, 2013

In this model agents meet, evaluate one another, decide whether or not to date, if and when to become sexual partners, and when to break up.

Roman Amphora reuse

Tom Brughmans | Published Wednesday, August 07, 2019 | Last modified Wednesday, March 15, 2023

UPDATE in V1.1.0: missing input data files added; relative paths to input data files changed to “../data/FILENAME”

A model that allows for representing key theories of Roman amphora reuse, to explore the differences in the distribution of amphorae, re-used amphorae and their contents.

This model generates simulated distributions of prime-use amphorae, primeuse contents (e.g. olive oil) and reused amphorae. These simulated distributions will differ between experiments depending on the experiment’s variable settings representing the tested theory: variations in the probability of reuse, the supply volume, the probability of reuse at ports. What we are interested in teasing out is what the effect is of each theory on the simulated amphora distributions.

Value Chain Marketing (VCM)

Stephanie Hintze | Published Monday, April 14, 2014 | Last modified Thursday, October 16, 2014

Inspired by the SKIN model, the basic concept here is to model the acceptance and implementation of supplier innovations. This model includes three types of agents comprising suppliers, manufacturers and applicators.

Displaying 10 of 942 results for "Jan Buurma" 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