Computational Model Library

Displaying 10 of 943 results for "J Van Der Beek" clear search

RobbyGA modified 2019

Timothy Gooding | Published Sunday, February 24, 2019

This is a modification of the RobbyGA model by the Santa Fe Institute (see model Info tab for full information). The basic idea is that the GA has been changed to one where the agents have a set lifetime, anyone can reproduce with anyone, but where there is a user-set amount of ‘starvation’ that kills the agents that have a too low fitness.

AMMA: Agent-based Model of the Media Arena

Annie Waldherr | Published Tuesday, February 11, 2014

The AMMA simulates how news waves emerge in the mass media. Drawing on the ideas of public arena models and issue-attention cycles, it represents fundamental principles of public communication in a virtual media system.

Expectation-Based Bayesian Belief Revision

C Merdes Momme Von Sydow Ulrike Hahn | Published Monday, June 19, 2017 | Last modified Monday, August 06, 2018

This model implements a Bayesian belief revision model that contrasts an ideal agent in possesion of true likelihoods, an agent using a fixed estimate of trusting its source of information, and an agent updating its trust estimate.

The model represents empirically observed recycling behaviour of Chinese citizens, based on the theory of reasoned action (TRA), the theory of planned behaviour (TPB) and the theory of planned behaviour extended with situational factors (TPB+).

This article presents an agent-based model of an Italian textile district where thousands of small firms specialize in particular phases of fabrics production. It reconstructs the web of communication between firms as they arrange production chains. In turn, production chains result in road traffic between the geographical areas on which the district extends. The reconstructed traffic exhibits a pattern that has been observed, but not foreseen, by policy makers.

Peer reviewed Minding Norms in an Epidemic Does Matter

Klaus G. Troitzsch | Published Saturday, February 27, 2021 | Last modified Monday, September 13, 2021

This paper tries to shed some light on the mutual influence of citizen behaviour and the spread of a virus in an epidemic. While the spread of a virus from infectious to susceptible persons and the outbreak of an infection leading to more or less severe illness and, finally, to recovery and immunity or death has been modelled with different kinds of models in the past, the influence of certain behaviours to keep the epidemic low and to follow recommendations of others to apply these behaviours has rarely been modelled. The model introduced here uses a theory of the effect of norm invocations among persons to find out the effect of spreading norms interacts with the progress of an epidemic. Results show that norm invocations matter. The model replicates the histories of the COVID-19 epidemic in various region, including “second waves” (but only until the end of 2021 as afterwards the official statistics ceased to be reliable as many infected persons did not report their positive test results after countermeasures were relieved), and shows that the calculation of the reproduction numbers from current reported infections usually overestimates the “real” but in practice unobservable reproduction number.

RefugeePathSIM Model

Liliana Perez Saeed Harati Guillaume Arnoux Hébert | Published Thursday, October 11, 2018 | Last modified Tuesday, October 16, 2018

RefugeePathSIM is an agent-based model to simulate the movement behavior of refugees in order to identify pathways of forced migration under crisis. The model generates migrants and lets them leave conflict areas for a destination that they choose based on their characteristics and desires. RefugeePathSIM has been developed and applied in a study of the Syrian war, using monthly data in years 2011-2015.

Sorghum supply development in Meru County, Kenya

Tim Verwaart Coen Van Wagenberg | Published Wednesday, September 06, 2017 | Last modified Thursday, May 30, 2019

Trust between farmers and processors is a key factor in developing stable supply chains including “bottom of the pyramid”, small-scale farmers. This simulation studies a case with 10000 farmers.

This is an Agent Based Model of a generic food chain network consisting of stylized individuals representing producers, traders, and consumers. It is developed to: 1/ to describe the dynamically changing disaggregated flows of crop items between these agents, and 2/ to be able to explicitly consider agent behavior. The agents have implicit personal objectives for trading. Resilience and efficiency are quantified using the ascendency concept by linking these to the fraction of fulfillment of the overall explicit objective to have all consumers meet their food requirement. Different types of network structures in combination with different agent interaction types under different types of stylized shocks can be simulated.

Displaying 10 of 943 results for "J Van Der Beek" clear search

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