Computational Model Library

Displaying 10 of 1164 results for "Aad Kessler" clear search

GoodBYE: BadYear Econometrics

Colin Wren Iza Romanowska | Published Thursday, December 26, 2024

A formalized implementation of Halstead and O’Shea’s Bad Year Economics. The agent population uses one of four resilience strategies in an attempt to cope with a dynamic environment of stresses and shocks.

Village Ecodynamics Project

ipem | Published Friday, May 13, 2011 | Last modified Saturday, April 27, 2013

The Village Project is designed to help archaeologists understand the factors influencing settlement patterns of small-scale agrarian peoples. Although such societies are becoming increasingly rare, they represent the norm throughout most of the Neolithic period the world over.

FlowLogo integrates agent-based and groundwater flow simulation. It aims to simplify the process of developing participatory ABMs in the groundwater space and begin the exploration of novel, bottom-up solutions to conflicts in shared aquifers.

Hybrid fish-plankton model

Gudrun Wallentin Christian Neuwirth | Published Friday, October 28, 2016 | Last modified Sunday, January 29, 2017

A hybrid predator-prey model of fish and plankton that switches dynamically between ABM and SD representations. It contains 6 related structural designs of the same model.

Team Cognition

Iris Lorscheid | Published Sunday, May 23, 2021

The teamCognition model investigates team decision processes by using an agent-based model to conceptualize team decisions as an emergent property. It uses a mixed-method research design with a laboratory experiment providing qualitative and quantitative input for the model’s construction, as well as data for an output validation of the model. The agent-based model is used as a computational testbed to contrast several processes of team decision making, representing potential, simplified mechanisms of how a team decision emerges. The increasing overall fit of the simulation and empirical results indicates that the modeled decision processes can at least partly explain the observed team decisions.

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. ...

Peer reviewed FishCensus

Miguel Pais | Published Tuesday, December 06, 2016 | Last modified Thursday, February 09, 2017

The FishCensus model simulates underwater visual census methods, where a diver estimates the abundance of fish. A separate model is used to shape species behaviours and save them to a file that can be shared and used by the counting model.

This model uses ’satisficing’ as a model for farmers’ decision making to learn about influences of alternative decision-making models on simulation results and to exemplify a way to transform a rather theoretical concept into a feasible decision-making model for agent-based farming models.

Opinion Dynamics Under Intergroup Conflict Escalation

Meysam Alizadeh Alin Coman Michael Lewis Katia Sycara | Published Friday, March 14, 2014 | Last modified Wednesday, October 29, 2014

We develop an agent-based model to explore the effect of perceived intergroup conflict escalation on the number of extremists. The proposed model builds on the 2D bounded confidence model proposed by Huet et al (2008).

Thermostat II

María Pereda Jesús M Zamarreño | Published Thursday, June 12, 2014 | Last modified Monday, June 16, 2014

A thermostat is a device that allows to have the temperature in a room near a desire value.

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