Computational Model Library

Displaying 10 of 147 results for "Andrea Rapisarda" clear search

Simulation of the Governance of Complex Systems

Fabian Adelt Johannes Weyer Robin D Fink Andreas Ihrig | Published Monday, December 18, 2017 | Last modified Friday, March 02, 2018

Simulation-Framework to study the governance of complex, network-like sociotechnical systems by means of ABM. Agents’ behaviour is based on a sociological model of action. A set of basic governance mechanisms helps to conduct first experiments.

Educational attainment and student retention in higher education are two of the main focuses of higher education research. Institutions in the U.S. are constantly looking for ways to identify areas of improvement across different aspects of the student experience on university campuses. This paper combines Department of Education data, U.S. Census data, and higher education theory on student retention, to build an agent-based model of student behavior.

Modeling information Asymmetries in Tourism

Rodolfo Baggio Jacopo Baggio | Published Monday, January 09, 2012 | Last modified Saturday, April 27, 2013

A very simple model elaborated to explore what may happens when buyers (travelers) have more information than sellers (tourist destinations)

Swidden farming by individual households

C Michael Barton | Published Sunday, April 27, 2008 | Last modified Saturday, April 27, 2013

Swidden Farming is designed to explore the dynamics of agricultural land management strategies.

The spatially-explicit AgriculTuralLandscApe Simulator (ATLAS) simulates realistic spatial-temporal crop availability at the landscape scale through crop rotations and crop phenology.

The Pampas Model is an Agent-Based Model intended to explore the dynamics of structural and land use changes in agricultural systems of the Argentine Pampas in response to climatic, technological economic, and political drivers.

The purpose of the OMOLAND-CA is to investigate the adaptive capacity of rural households in the South Omo zone of Ethiopia with respect to variation in climate, socioeconomic factors, and land-use at the local level.

This model simulations social and childcare provision in the UK. Agents within simulated households can decide to provide for informal care, or pay for private care, for their loved ones after they have provided for childcare needs. Agents base these decisions on factors including their own health, employment status, financial resources, relationship to the individual in need and geographical location. This model extends our previous simulations of social care by simulating the impact of childcare demand on social care availability within households, which is known to be a significant constraint on informal care provision.

Results show that our model replicates realistic patterns of social and child care provision, suggesting that this framework can be a valuable aid to policy-making in this area.

Agent-based model of team decision-making in hidden profile situations

Jonas Stein Andreas Flache Vincenz Frey | Published Thursday, April 20, 2023 | Last modified Friday, November 17, 2023

The model presented here is extensively described in the paper ‘Talk less to strangers: How homophily can improve collective decision-making in diverse teams’ (forthcoming at JASSS). A full replication package reproducing all results presented in the paper is accessible at https://osf.io/76hfm/.

Narrative documentation includes a detailed description of the model, including a schematic figure and an extensive representation of the model in pseudocode.

The model develops a formal representation of a diverse work team facing a decision problem as implemented in the experimental setup of the hidden-profile paradigm. We implement a setup where a group seeks to identify the best out of a set of possible decision options. Individuals are equipped with different pieces of information that need to be combined to identify the best option. To this end, we assume a team of N agents. Each agent belongs to one of M groups where each group consists of agents who share a common identity.
The virtual teams in our model face a decision problem, in that the best option out of a set of J discrete options needs to be identified. Every team member forms her own belief about which decision option is best but is open to influence by other team members. Influence is implemented as a sequence of communication events. Agents choose an interaction partner according to homophily h and take turns in sharing an argument with an interaction partner. Every time an argument is emitted, the recipient updates her beliefs and tells her team what option she currently believes to be best. This influence process continues until all agents prefer the same option. This option is the team’s decision.

This is code repository for the paper “Homophily as a process generating social networks: insights from Social Distance Attachment model”.
It provides all information, code and data necessary to replicate all the simulations and analyses presented in the paper.
This document contains the overall instruction as well as description of the content of the repository.
Details regarding particular stages are documented within source files as comments.

Displaying 10 of 147 results for "Andrea Rapisarda" clear search

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