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Analyzed about 18 hours ago. based on code collected about 18 hours ago.

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%
8 Other
11%

30 Day Summary

Jan 21 2018 — Feb 20 2018

12 Month Summary

Feb 20 2017 — Feb 20 2018
  • 24 Commits
    Up + 9 (60%) from previous 12 months
  • 7 Contributors
    Up + 1 (16%) from previous 12 months