hmep: HMEP Multi Expression Programming – a genetic programming variant

[ ai, bsd3, library, program ] [ Propose Tags ]

A multi expression programming implementation with focus on speed.

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Versions [faq] 0.0.0, 0.0.1, 0.1.0, 0.1.1
Dependencies base (>=4.7 && <5), containers, hmatrix, hmep, mersenne-random-pure64, monad-mersenne-random, random, vector [details]
License BSD-3-Clause
Copyright 2017 Bogdan Penkovsky
Author Bogdan Penkovsky
Maintainer dev at penkovsky dot com
Category AI
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Source repo head: git clone
Uploaded by penkovsky at Fri Oct 6 22:37:54 UTC 2017
Distributions NixOS:0.1.1
Executables hmep-demo
Downloads 859 total (24 in the last 30 days)
Rating 2.0 (votes: 1) [estimated by rule of succession]
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Status Hackage Matrix CI
Docs uploaded by user [build log]
All reported builds failed as of 2017-10-06 [all 1 reports]




Maintainer's Corner

For package maintainers and hackage trustees

Readme for hmep-0.0.0

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Multi Expression Programming

You say, Haskell has not enough machine learning libraries?

Here is yet another one!


There exist many other Genetic Algorithm (GA) Haskell packages. Personally I have used simple genetic algorithm, GA, and moo for quite a long time. The last package was the most preferred, but the other two are also great.

However, when I came up with this MEP paper, to my surprise there was no MEP realization in Haskell. Soon I realized that existing GA packages are limited, and it would be more efficient to implement MEP from scratch.

That is how this package was started. I also wish to say thank you to the authors of the moo GA library, which inspired the present hmep package.

About MEP

Multi Expression Programming is a genetic programming variant encoding multiple solutions in the same chromosome. A chromosome is a computer program. Each gene is featuring code reuse. For more details, please check and