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Michigan-style Learning Classifier Systems

Project description


What is Piecewise?

A Michigan-style Learning Classifier System (LCS) library, written in Python.

It makes heavy use of object-oriented language features to provide a modular, extensible framework on which to build LCS algorithms.

The currently implemented algorithms are:

  1. XCS (ternary rule representation)
  2. XCSR (centre-spread rule representation)

Project Philosophy

The primary use case of Piecewise is for LCS researchers who are interested in:

  1. Investigating modifications or extensions to existing LCS algorithms.
  2. Running experiments with LCS algorithms on common environments, through a standardised and easy-to-use interface.

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