Computational Model Library

Displaying 10 of 258 results for "Philipp S. Sommer" clear search

Peer reviewed Swidden Farming Version 2.0

C Michael Barton | Published Wednesday, June 12, 2013 | Last modified Wednesday, September 03, 2014

Model of shifting cultivation. All parameters can be controlled by the user or the model can be run in adaptive mode, in which agents innovate and select parameters.

The Urban Traffic Simulator is an agent-based model developed in the Unity platform. The model allows the user to simulate several autonomous vehicles (AVs) and tune granular parameters such as vehicle downforce, adherence to speed limits, top speed in mph and mass. The model allows researchers to tune these parameters, run the simulator for a given period and export data from the model for analysis (an example is provided in Jupyter Notebook).

The data the model is currently able to output are the following:

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.

FLOSSSim: An Agent-Based Model of the Free/Libre Open Source Software (FLOSS) Development Process

Nicholas Radtke | Published Saturday, December 31, 2011 | Last modified Saturday, April 27, 2013

An agent-based model of the Free/Libre Open Source Software (FLOSS) development process designed around agents selecting FLOSS projects to contribute to and/or download.

Dental Routine Check-Up

Peyman Shariatpanahi Afshin Jafari | Published Thursday, March 10, 2016 | Last modified Monday, April 08, 2019

We develop an agent-based model for collective behavior of routine medical check-ups, and specifically dental visits, in a social network.

Modeling Personal Carbon Trading with ABM

Roman Seidl | Published Friday, December 07, 2018 | Last modified Thursday, July 29, 2021

A simulated approach for Personal Carbon Trading, for figuring out what effects it might have if it will be implemented in the real world. We use an artificial population with some empirical data from international literature and basic assumptions about heterogeneous energy demand. The model is not to be used as simulating the actual behavior of real populations, but a toy model to test the effects of differences in various factors such as number of agents, energy price, price of allowances, etc. It is important to adapt the model for specific countries as carbon footprint and energy demand determines the relative success of PCT.

A model for simulating the evolution of individual’s preferences, incliding adaptive agents “falsifying” -as public opinions- their own preferences. It was builded to describe, explore, experiment and understand how simple heuristics can modulate global opinion dynamics. So far two mechanisms are implemented: a version of Festiguer’s reduction of cognitive disonance, and a version of Goffman’s impression management. In certain social contexts -minority, social rank presure- some models agents can “fake” its public opinion while keeping internally the oposite preference, but after a number of rounds following this falsifying behaviour pattern, a coherence principle can change the real or internal preferences close to that expressed in public.

ViSA 2.0.0 is an updated version of ViSA 1.0.0 aiming at integrating empirical data of a new use case that is much smaller than in the first version to include field scale analysis. Further, the code of the model is simplified to make the model easier and faster. Some features from the previous version have been removed.
It simulates decision behaviors of different stakeholders showing demands for ecosystem services (ESS) in agricultural landscape. It investigates conditions and scenarios that can increase the supply of ecosystem services while keeping the viability of the social system by suggesting different mixes of initial unit utilities and decision rules.

Peer reviewed WaDemEsT-Water Demand Estimation Tool for Residential Areas

Kamil Aybuğa | Published Tuesday, February 18, 2025

This model simulates household water consumption patterns in an urban environment. Its current setup compares monthly water consumption data, and the results of a daily heuristic water demand model with the simulation results produced by household demographics that is fine tuned via some base demand model. It’s designed to estimate and analyze water demand based on various factors including household demographics, daily routines of residents (working, weekending, vacation patterns), weather conditions (temperature and precipitation), appliance usage patterns, seasonal variations, and special periods such as weekends and holidays. The model aims to help understand how different factors influence residential water consumption and can be used for water demand forecasting and management.

Market for Protection

Steven Doubleday | Published Monday, July 01, 2013 | Last modified Monday, August 19, 2013

Simulation to replicate and extend an analytical model (Konrad & Skaperdas, 2010) of the provision of security as a collective good. We simulate bandits preying upon peasants in an anarchy condition.

Displaying 10 of 258 results for "Philipp S. Sommer" clear search

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