Computational Model Library

Displaying 10 of 893 results for "Am Vaes - Van De Hulsbeek" clear search

Dynamic Interbank Network Simulator

Valentina Guleva | Published Wednesday, November 23, 2016 | Last modified Monday, April 13, 2020

The model provides instruments for the simulation of interbank network evolution. There are tools for dynamic network analysis, allowing to evaluate graph topological invariants, thermodynamic network features and combinational node-based features.

SBH trust model

Di Wang | Published Tuesday, December 14, 2010 | Last modified Saturday, April 27, 2013

This is a computational model to articulate the theory and test some assumption and axioms for the trust model and its relationship to SBH.

Societal Simulator v203

Tim Gooding | Published Tuesday, October 01, 2013 | Last modified Friday, November 28, 2014

Designed to capture the evolutionary forces of global society.

This model simulates the heterogeneity of preferences in a PG game and how the interaction between them affects the dynamics of voluntary contributions. Model is based on the results of a human-based experiment.

Growing Unpopular Norms. A Network-Situated ABM of Norm Choice.

C Merdes | Published Tuesday, November 22, 2016 | Last modified Saturday, March 17, 2018

The model’s purpose is to provide a potential explanation for the emergence, sustenance and decline of unpopular norms based on pluralistic ignorance on a social network.

The Informational Dynamics of Regime Change

Dominik Klein Johannes Marx | Published Saturday, October 07, 2017 | Last modified Tuesday, January 14, 2020

We model the epistemic dynamics preceding political uprising. Before deciding whether to start protests, agents need to estimate the amount of discontent with the regime. This model simulates the dynamics of group knowledge about general discontent.

Transhumants move their herds based on strategies simultaneously considering several environmental and socio-economic factors. There is no agreement on the influence of each factor in these strategies. In addition, there is a discussion about the social aspect of transhumance and how to manage pastoral space. In this context, agent-based modeling can analyze herd movements according to the strategy based on factors favored by the transhumant. This article presents a reductionist agent-based model that simulates herd movements based on a single factor. Model simulations based on algorithms to formalize the behavioral dynamics of transhumants through their strategies. The model results establish that vegetation, water outlets and the socio-economic network of transhumants have a significant temporal impact on transhumance. Water outlets and the socio-economic network have a significant spatial impact. The significant impact of the socio-economic factor demonstrates the social dimension of Sahelian transhumance. Veterinarians and markets have an insignificant spatio-temporal impact. To manage pastoral space, water outlets should be at least 15 km
from each other. The construction of veterinary centers, markets and the securitization of transhumance should be carried out close to villages and rangelands.

Fertility Tradeoffs

Kristin Crouse | Published Tuesday, November 05, 2019 | Last modified Thursday, April 06, 2023

Fertility Tradeoffs is a NetLogo model that illustrates the emergencent tradeoffs between the quality and quantity of offspring. Often, we associate high fitness with maximizing the number of offspring. However, under certain circumstances, it pays instead to optimize the number of offspring, having fewer offspring than is possible. When the number of offspring is reduced, more energy can be invested in each offspring, which can have fitness benefits.

01a ModEco V2.05 – Model Economies – In C++

Garvin Boyle | Published Monday, February 04, 2013 | Last modified Friday, April 14, 2017

Perpetual Motion Machine - A simple economy that operates at both a biophysical and economic level, and is sustainable. The goal: to determine the necessary and sufficient conditions of sustainability, and the attendant necessary trade-offs.

The purpose of this model is explore how “friend-of-friend” link recommendations, which are commonly used on social networking sites, impact online social network structure. Specifically, this model generates online social networks, by connecting individuals based upon varying proportions of a) connections from the real world and b) link recommendations. Links formed by recommendation mimic mutual connection, or friend-of-friend algorithms. Generated networks can then be analyzed, by the included scripts, to assess the influence that different proportions of link recommendations have on network properties, specifically: clustering, modularity, path length, eccentricity, diameter, and degree distribution.

Displaying 10 of 893 results for "Am Vaes - Van De Hulsbeek" clear search

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