MOSES -- Meta-Optimizing Semantic Evolutionary Search

opencog	singnet

MOSES is a machine-learning tool; it is an "evolutionary program learner". It is capable of learning short programs that capture patterns in input datasets. These programs can be output in either the Atomese programming language, or in python. For a given data input, the programs will roughly recreate the dataset on which they were trained.

MOSES has been used in several commercial applications, including the analysis of medical physician and patient clinical data, and in several different financial systems. It is also used by OpenCog to learn automated behaviors, movements and actions in response to perceptual stimulus of artificial-life virtual agents (i.e. pet-dog game avatars). Future plans including using it to learn behavioral programs that control real-world robots, via the OpenPsi implementation of Psi-theory and ROS nodes running on the OpenCog AtomSpace.

The term "evolutionary" means that MOSES uses genetic programming techniques to "evolve" new programs. Each program can be thought of as a tree (similar to a "decision tree", but allowing intermediate nodes to be any programming-language construct). Evolution proceeds by selecting one exemplar tree from a collection of reasonably fit individuals, and then making random alterations to the program tree, in an attempt to find an even fitter (more accurate) program.

It is derived from the ideas forumlated in Moshe Looks' PhD thesis, "Competent Program Evolution", 2006 (Washington University, Missouri). Moshe is also one of the primary authors of this code.

A short example, from begining to end, can be found in this Jupyter notebook (courtesy Robert Haas, for the Mevis plot package.)

License

MOSES is under double license, Apache 2.0 and GNU AGPL 3.

Documentation

Documentation can be found in the /docs directory, which includes a "QuickStart.pdf" that reviews the algorithms and data structures used within MOSES. A detailed man-page can be found in /moses/moses/man/moses.1. There is also a considerable amount of information in the OpenCog wiki: http://wiki.opencog.org/w/Meta-Optimizing_Semantic_Evolutionary_Search

Prerequisites

To build and run MOSES, the packages listed below are required. With a few exceptions, most Linux distributions will provide these packages.

boost

C++ utilities package http://www.boost.org/ | libboost-dev

cmake

Build management tool; v2.8 or higher recommended. http://www.cmake.org/ | cmake

cxxtest

Unit test framework http://cxxtest.sourceforge.net/ | https://launchpad.net/~opencog-dev/+archive/ppa | cxxtest

guile

Embedded scheme REPL (version 3.0 or newer is required). http://www.gnu.org/software/guile/guile.html

cogutil

Common OpenCog C++ utilities http://github.com/opencog/cogutil It uses exactly the same build procedure as this package. Be sure to sudo make install at the end.

atomspace

OpenCog Atomspace graph database http://github.com/opencog/atomspace It uses exactly the same build procedure as this package. Be sure to sudo make install at the end.

ure

OpenCog Unified Rule Engine http://github.com/opencog/ure It uses exactly the same build procedure as this package. Be sure to sudo make install at the end.

Optional Prerequisites

The following packages are optional. If they are not installed, some optional parts of MOSES will not be built. The CMake command, during the build, will be more precise as to which parts will not be built.

MPI

Message Passing Interface Required for compute-cluster version of MOSES Use either MPICHV2 or OpenMPI | http://www.open-mpi.org/ | libopenmpi-dev

Building MOSES

Perform the following steps at the shell prompt:

    cd to project root dir
    mkdir build
    cd build
    cmake -DCMAKE_BUILD_TYPE=Release ..
    make

Libraries will be built into subdirectories within build, mirroring the structure of the source directory root. The flag -DCMAKE_BUILD_TYPE=Release results in binaries that are optimized for for performance; ommitting this flag will result in faster builds, but slower executables.

Unit tests

To build and run the unit tests, from the ./build directory enter (after building moses as above):

    make test

Installation

Just say sudo make install after finishing the build.

Examples

Please see the examples directory.