Educational Learning Classifier System (eLCS) - Implementation of a basic, generic Michigan-style LCS algorithm
Please see included eLCS_Guide.pdf for README details.
Requirements: eLCS requires python 3.0 or greater. Anaconda is recommended.
eLCS: includes 5 separate algorithm implementations labeled as Demo 1-5, along with additional files labled as Demo 0.
Each of the 5 implementations build upon the previous one, adding essential components of an LCS algorithm in steps to highlight how
such algorithms work, and how they can be implemented. Each implementation is intended to be run using the respective eLCS_Run.py file.
python ./eLCS_Run.py
Users are intended to observe the standard out from theses runs as well as the output files generated from these runs that will appear in the respective 'Local_Output' folder. A few example datasets are provided in 'Demo_Datasets'.