Computational Model Library

Displaying 10 of 75 results for "Nicole Rogge" clear search

A Multi-Agent Simulation Approach to Farmland Auction Markets

James Nolan | Published Wednesday, June 22, 2011 | Last modified Saturday, April 27, 2013

This model explores the effects of agent interaction, information feedback, and adaptive learning in repeated auctions for farmland. It gathers information for three types of sealed-bid auctions, and one English auction and compares the auctions on the basis of several measures, including efficiency, price information revelation, and ability to handle repeated bidding and agent learning.

A Model to Unravel the Complexity of Rural Food Security

Stefano Balbi Samantha Dobbie | Published Monday, August 22, 2016 | Last modified Sunday, December 02, 2018

An ABM to simulate the behaviour of households within a village and observe the emerging properties of the system in terms of food security. The model quantifies food availability, access, utilisation and stability.

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.

A fisher directed management system was describeded by Hart (2021). It was proposed that fishers should only be allowed to exploit a resource if they collaborated in a resource management system for which they would own and be collectively responsible for. As part of the system fishers would need to follow the rules of exploitation set by the group and provide a central unit with data with which to monitor the fishery. Any fisher not following the rules would at first be fined but eventually expelled from the fishery if he/she continued to act selfishly. This version of the model establishes the dynamics of a fleet of vessels and controls overfishing by imposing fines on fishers whose income is low and who are tempted to keep fishing beyond the set quota which is established each year depending on the abundance of the fish stock. This version will later be elaborated to have interactions between the fishers including pressure to comply with the norms set by the group and which could lead to a stable management system.

Last Mile Commuter Behavior Model

Dean Massey Moira Zellner Yoram Shiftan Jonathan Levine Maria Arquero | Published Friday, November 07, 2014 | Last modified Friday, November 07, 2014

We represent commuters and their preferences for transportation cost, time and safety. Agents assess their options via their preferences, their environment, and the modes available. The model has policy levers to test impact on last-mile problem.

The model represents urban commuters’ transport mode choices among cars, public transit, and motorcycles—a mode highly prevalent in developing countries. Using an agent-based modeling approach, it simulates transport dynamics and serves as a testbed for evaluating policies aimed at improving mobility.

The model simulates an ecosystem of human agents who decide, at each time step, which mode of transportation to use for commuting to work. Their decision is based on a combination of personal satisfaction with their most recent journey—evaluated across a vector of individual needs—the information they crowdsource from their social network, and their personal uncertainty regarding trying new transport options.

Agents are assigned demographic attributes such as sex, age, and income level, and are distributed across city neighborhoods according to their socioeconomic status. To represent social influence in decision-making, agents are connected via a scale-free social network topology, where connections are more likely among agents within the same socioeconomic group, reflecting the tendency of individuals to form social ties with similar others.

Crowdworking Model

Georg Jäger | Published Wednesday, September 25, 2019

The purpose of this agent-based model is to compare different variants of crowdworking in a general way, so that the obtained results are independent of specific details of the crowdworking platform. It features many adjustable parameters that can be used to calibrate the model to empirical data, but also when not calibrated it yields essential results about crowdworking in general.
Agents compete for contracts on a virtual crowdworking platform. Each agent is defined by various properties like qualification and income expectation. Agents that are unable to turn a profit have a chance to quit the crowdworking platform and new crowdworkers can replace them. Thus the model has features of an evolutionary process, filtering out the ill suited agents, and generating a realistic distribution of agents from an initially random one. To simulate a stable system, the amount of contracts issued per day can be set constant, as well as the number of crowdworkers. If one is interested in a dynamically changing platform, the simulation can also be initialized in a way that increases or decreases the number of crowdworkers or number of contracts over time. Thus, a large variety of scenarios can be investigated.

Model of diffusion of vegetarian diets coupling ABM and argumentation framework

This generic agent-based model simulates the evolution of agent’s opinions through their exchange of arguments.
The idea behind this model is to explicitly represent the process of mental deliberation of agents from arguments to an opinion, through the use of Dung’s argumentation framework complemented by a structured description of arguments. An application of the model on the diffusion of vegetarian diets is proposed.

Peer reviewed PolicySpace2: modeling markets and endogenous public policies

Bernardo Furtado | Published Thursday, February 25, 2021 | Last modified Friday, January 14, 2022

Policymakers decide on alternative policies facing restricted budgets and uncertain future. Designing public policies is further difficult due to the need to decide on priorities and handle effects across policies. Housing policies, specifically, involve heterogeneous characteristics of properties themselves and the intricacy of housing markets and the spatial context of cities. We propose PolicySpace2 (PS2) as an adapted and extended version of the open source PolicySpace agent-based model. PS2 is a computer simulation that relies on empirically detailed spatial data to model real estate, along with labor, credit, and goods and services markets. Interaction among workers, firms, a bank, households and municipalities follow the literature benchmarks to integrate economic, spatial and transport scholarship. PS2 is applied to a comparison among three competing public policies aimed at reducing inequality and alleviating poverty: (a) house acquisition by the government and distribution to lower income households, (b) rental vouchers, and (c) monetary aid. Within the model context, the monetary aid, that is, smaller amounts of help for a larger number of households, makes the economy perform better in terms of production, consumption, reduction of inequality, and maintenance of financial duties. PS2 as such is also a framework that may be further adapted to a number of related research questions.

Displaying 10 of 75 results for "Nicole Rogge" clear search

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