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README
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MOSES Documentation
===================
MOSES Version 3.0 -- March 2012
Copyright 2005-2008, Moshe Looks and Novamente LLC
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
********
Overview
********
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 .
**********************
Code and Documentation
**********************
The code for reproducing all of the published experiments on MOSES
may be found in the learning/moses subdirectory.
Below is a list of publications on MOSES. The QuickGuide.pdf file in
this directory provides an overview of the MOSES alorithms and the main
structures and routines in the source code. In addition, documentation
may be found here:
moses/moses/man -- a unix 'manual' page describing the executable.
moses/moses/documentation -- algorthm insights
moses/moses/diary -- a diary of experimental results
************
Installation
************
You need to have a recent gcc (4.5 or newer), the boost libraries
(version 1.44 or newer, http://www.boost.org) and the CMake package
(http://www.cmake.org/HTML/Index.html).
Create a directory called "build" in the root folder, then cd to it.
Run "cmake .." in this directory. This will create the needed
makefiles. Then, make the project using "make" (from the build
directory).
Generated executables will be in the folder build/learning/moses/main.
*********************
Publications on MOSES
*********************
1. Moshe Looks, "Scalable Estimation-of-Distribution Program Evolution",
Genetic and Evolutionary Computation COnference (GECCO), 2007.
2. Moshe Looks, "On the Behavioral Diversity of Random Programs", Genetic and
Evolutionary Computation COnference (GECCO), 2007.
3. Moshe Looks, "Meta-Optimizing Semantic Evolutionary Search", Genetic and
Evolutionary Computation COnference (GECCO), 2007.
4. Moshe Looks, Ben Goertzel, Lucio de Souza Coelho, Mauricio Mudado, and
Cassio Pennachin,"Clustering Gene Expression Data via Mining Ensembles of
Classification Rules Evolved Using MOSES", Genetic and Evolutionary
Computation COnference (GECCO), 2007.
5. Moshe Looks, Ben Goertzel, Lucio de Souza Coelho, Mauricio Mudado, and
Cassio Pennachin, "Understanding Microarray Data through Applying Competent
Program Evolution", Genetic and Evolutionary Computation COnference (GECCO),
2007.
6. Moshe Looks, "Competent Program Evolution" Doctoral Dissertation, Washington
University in St. Louis, 2006.
7. Moshe Looks, "Program Evolution for General Intelligence", Artificial
General Intelligence Research Institute Workshop (AGIRI), 2006.