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Distributed Evolutionary Computation framework

Project description

Componentized Machine Learning system whose design is mainly based on
Evolutionary Computation ideas, especially Memetic Computing: building blocks
are ``Replicators`` that evolve in a potentially networked environment.

The goal of EvoGrid is to provide a pluggable framework (based on the Zope
Component Architecture) and reuse as much as possible existing ML algorithms
implementations (either in Python or other language as long as the can be
wrapped into a pythonic component).

The project is currently at an early development stage providing only
implementation for base evolutionary components (not GRID / networking support
yet).

For more details of what is included and what is planned, please refer to the
launchpad project page at https://launchpad.net/products/evogrid .

To get started with evogrid, please read the HTML rendered doctests published on
the homepage and especially the main tutorial at:
http://champiland.homelinux.net/evogrid/doc/components_overview.html

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