About the CoMSES Model Library more info
Our mission is to help computational modelers develop, document, and share their computational models in accordance with community standards and good open science and software engineering practices. Model authors can publish their model source code in the Computational Model Library with narrative documentation as well as metadata that supports open science and emerging norms that facilitate software citation, computational reproducibility / frictionless reuse, and interoperability. Model authors can also request private peer review of their computational models. Models that pass peer review receive a DOI once published.
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 feel free to 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 detailed metadata on availability of code and bibliometric information on the landscape of ABM/IBM publications that we welcome you to explore.
Displaying 4 of 4 results behavioral game theory clear search
Peer reviewed Evolutionary Economic Learning Simulation: A Genetic Algorithm for Dynamic 2x2 Strategic-Form Games in Python
Vinicius Ferraz Thomas Pitz | Published Friday, April 08, 2022This project combines game theory and genetic algorithms in a simulation model for evolutionary learning and strategic behavior. It is often observed in the real world that strategic scenarios change over time, and deciding agents need to adapt to new information and environmental structures. Yet, game theory models often focus on static games, even for dynamic and temporal analyses. This simulation model introduces a heuristic procedure that enables these changes in strategic scenarios with Genetic Algorithms. Using normalized 2x2 strategic-form games as input, computational agents can interact and make decisions using three pre-defined decision rules: Nash Equilibrium, Hurwicz Rule, and Random. The games then are allowed to change over time as a function of the agent’s behavior through crossover and mutation. As a result, strategic behavior can be modeled in several simulated scenarios, and their impacts and outcomes can be analyzed, potentially transforming conflictual situations into harmony.
Simulation of Self-enforcing Agreement in Cooperative Teams
Hang Xiong | Published Friday, April 01, 2016This is an agent-based model of the implementation of the self-enforcing agreement in cooperative teams.
A Model of Iterated Ultimatum game
Andrea Scalco | Published Tuesday, February 24, 2015 | Last modified Monday, March 09, 2015The simulation generates two kinds of agents, whose proposals are generated accordingly to their selfish or selfless behaviour. Then, agents compete in order to increase their portfolio playing the ultimatum game with a random-stranger matching.
MASTOC - A Multi-Agent System of the Tragedy Of The Commons
Julia Schindler | Published Tuesday, November 30, 2010 | Last modified Saturday, April 27, 2013MASTOC is a replication of the Tragedy of the Commons by G. Hardin, programmed in NetLogo 4.0.4, based on behavioral game theory and Nash solution.