DEAP 0.9.1 / 1.0.0 RC 2

Evolutionary computation framework for fast prototyping and testing of ideas
DEAP - An example of how the DEAP evolutionary computation framework can be used in a Python script.
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DEAP (Distributed Evolutionary Algorithms in Python) is a free, open-source and cross-platform evolutionary computation framework that allows you to quickly perform prototyping processes and testing of ideas.

DEAP aims to make algorithms easy to understand and data structures transparent, and implements intuitive parallelism, eliminating the unnecessary implementation details.

Detailed instructions on how to install and use the DEAP utility on your Mac are available HERE.

DEAP is cross-platform and it works on Mac OS X, Windows and Linux.

Main features:

  • Provides an environment to quickly implement algorithm
  • Allow for straightforward parallelization
  • Substantial set of real-world examples

last updated on:
July 31st, 2013, 20:45 GMT
file size:
969 KB
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operating system(s):
Mac OS X
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What's New in version 1.0.0 RC 2
  • Better documentation of Logbook and Multistatistics.
  • New example of XKCD Knapsack using collections.Counter (ga/
  • Fitness can now be printed (str) ou represented (repr) even if it does not have values (Issue #20).
  • Remove no longer images from documentation, resulting in a small source archive.
read full changelog

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