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Project Summary

Meta-optimizing semantic evolutionary search (MOSES) is a new approach to program evolution, based on representation-building and probabilistic modeling. MOSES has been successfully applied to solve hard problems in domains such as computational biology, sentiment evaluation, and agent control. Results tend to be more accurate, and require less objective function evaluations, in comparison to other program evolution systems. Best of all, the result of running MOSES is not a large nested structure or numerical vector, but a compact and comprehensible program written in a simple Lisp-like mini-language.

For more information see: http://metacog.org/doc.html.

Interested C++ developers, please drop in at #opencog on IRC.freenode.net.

Tags

artificialintelligence combinatorylogic evolutionaryalgorithm evolutionarycomputation evolutionaryprogramming geneticalgorithm geneticprogramming machinelearning particleswarmoptimization programevolution

In a Nutshell, moses...

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C++
89%
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30 Day Summary

Oct 16 2018 — Nov 15 2018

12 Month Summary

Nov 15 2017 — Nov 15 2018
  • 13 Commits
    Down -9 (40%) from previous 12 months
  • 5 Contributors
    Down -2 (28%) from previous 12 months