About the CoMSES Model Library more info
Our mission is to help computational modelers at all levels engage in the establishment and adoption of community standards and good practices for developing and sharing computational models. Model authors can freely publish their model source code in the Computational Model Library alongside narrative documentation, open science metadata, and other emerging open science norms that facilitate software citation, reproducibility, interoperability, and reuse. Model authors can also request peer review of their computational models to receive a DOI.
All users of models published in the library must cite model authors when they use and benefit from their code.
Please check out our model publishing tutorial and contact us if you have any questions or concerns about publishing your model(s) in the Computational Model Library.
We also maintain a curated database of over 7500 publications of agent-based and individual based models with additional detailed metadata on availability of code and bibliometric information on the landscape of ABM/IBM publications that we welcome you to explore.
Displaying 3 of 3 results for 'Christoph Merdes'
AMIRIS
Kristina Nienhaus Christoph Schimeczek Ulrich Frey Evelyn Sperber Seyedfarzad Sarfarazi Felix Nitsch Johannes Kochems Aboubakr Achraf El Ghazi | Published Thursday, February 03, 2022AMIRIS is the Agent-based Market model for the Investigation of Renewable and Integrated energy Systems.
It is an agent-based simulation of electricity markets and their actors.
AMIRIS enables researches to analyse and evaluate energy policy instruments and their impact on the actors involved in the simulation context.
Different prototypical agents on the electricity market interact with each other, each employing complex decision strategies.
AMIRIS allows to calculate the impact of policy instruments on economic performance of power plant operators and marketers.
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Expectation-Based Bayesian Belief Revision
C Merdes Ulrike Hahn Momme Von Sydow | Published Monday, June 19, 2017 | Last modified Monday, August 06, 2018This 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.
Growing Unpopular Norms. A Network-Situated ABM of Norm Choice.
C Merdes | Published Tuesday, November 22, 2016 | Last modified Saturday, March 17, 2018The 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.