Michigan-style Learning Classifier Systems
Project description
Piecewise
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:
- XCS (ternary rule representation)
- XCSR (centre-spread rule representation)
Project Philosophy
The primary use case of Piecewise is for LCS researchers who are interested in:
- Investigating modifications or extensions to existing LCS algorithms.
- Running experiments with LCS algorithms on common environments, through a standardised and easy-to-use interface.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
No source distribution files available for this release.See tutorial on generating distribution archives.
Built Distribution
Close
Hashes for piecewise-0.1.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 45f35bb670ae6b8bde9bbf90f3b7cd3eb68004611adfd21e02f1ae22e7798f7c |
|
MD5 | 6ce2fe48bf5b6900ff11cdcdf73d87e5 |
|
BLAKE2b-256 | ad3d62c12ceb0ba9a2814390c018515d4906020703ab8061300221262c7c4092 |