Computational Model Library

Creating Intelligent Agents (version 1.0.0)

This model was developed to test the usability of evolutionary computing and reinforcement learning by extending a well known agent-based model. Sugarscape (Epstein & Axtell, 1996) has been used to demonstrate migration, trade, wealth inequality, disease processes, sex, culture, and conflict. It is on conflict that this model is focused to demonstrate how machine learning methodologies could be applied.

The code is based on the Sugarscape 2 Constant Growback model, availble in the NetLogo models library. New code was added into the existing model while removing code that was not needed and modifying existing code to support the changes. Support for the original movement rule was retained while evolutionary computing, Q-Learning, and SARSA Learning were added.

GUI-20200602.png

Release Notes

Initial release. A conference paper discussing the use of this model will be released at the The Computational Social Science Society of the Americas CSS 2020 conference in October 2020.

Version Submitter First published Last modified Status
1.0.0 Dale Brearcliffe Fri Sep 25 12:51:54 2020 Fri Sep 25 12:51:54 2020 Published

Discussion

Download Release
This website uses cookies and Google Analytics to help us track user engagement and improve our site. If you'd like to know more information about what data we collect and why, please see our data privacy policy. If you continue to use this site, you consent to our use of cookies.