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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%
8 Other
11%

30 Day Summary

Mar 24 2018 — Apr 23 2018

12 Month Summary

Apr 23 2017 — Apr 23 2018
  • 24 Commits
    Up + 9 (60%) from previous 12 months
  • 7 Contributors
    Up + 1 (16%) from previous 12 months