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MM-NEAT version 2.0 is no longer supported. Please get MM-NEAT 3+ from https://github.com/schrum2/MM-NEAT
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batch
data
lib
src
vizdoom
.classpath
.gitattributes
.gitignore
.project
HumanStudy-3DObjectBreederVs3DAnimationBreeder.bat
HumanStudy-PicbreederVsAnimationBreeder.bat
INTERACTIVE_EVOLUTION.txt
LICENSE.txt
MM-NEATv2.iml
PUBLICATIONS.txt
README.txt
TUTORIAL.txt
_vizdoom.ini
build.xml
copyright.txt
launchMultiple.bat
launchMultipleAsynchronously.bat
manifest.mf
postAllBestObjectiveWatch.bat
postAllBestObjectiveWatchStepByStep.bat
postAllCoOpTeamsWatch.bat
postBestEval.bat
postBestObjectiveEval.bat
postBestObjectiveEvalGeneration.bat
postBestObjectiveEvalMultiPop.bat
postBestObjectiveEvalTeam.bat
postBestObjectiveWatch.bat
postBestObjectiveWatchGeneration.bat
postBestObjectiveWatchLines.bat
postBestObjectiveWatchMultiPop.bat
postBestObjectiveWatchStepByStep.bat
postBestObjectiveWatchTeam.bat
postBestWatch.bat
postBoardGameBenchmarkAllPopHumanWatch.bat
postBoardGameBenchmarkBestHumanWatch.bat
postBoardGameBenchmarkBestOthelloWPCEval.bat
postBoardGameBenchmarkBestOthelloWPCWatch.bat
postLineage.bat
postParetoFrontWatch.bat
postProcess.bat
vizdoom.ini

README.txt

This version of MM-NEAT is not longer being developed. 
Please get the latest version from https://github.com/schrum2/MM-NEAT

MM-NEAT version 2.0

Copyright (c) 2014 The University of Texas at Austin 
and 2016 Southwestern University.
All rights reserved.
Refer to LICENSE.txt for detailed license information.
Also see copyright.txt for copyright information about the
included Ms. Pac-Man code.

WEBPAGE

http://nn.cs.utexas.edu/?mm-neat
Although, the latest version is on GitHub:
https://github.com/schrum2/MM-NEATv2

ABOUT

MM-NEAT stands for Multiobjective Modular Neuro-Evolution of Augmenting Topologies.
It is inspired by the original NEAT, but also incorporates multiobjective evolution
via NSGA-II, and supports several forms of modular neural networks. Support for
the fitness shaping technique Targeting Unachieved Goals (TUG) is also included.
Indirect encoding via HyperNEAT is also supported, as is interactive evolution of
several types of interesting artifacts (pictures, sounds, animations). The code was 
originally developed by Jacob Schrum (schrum2@southwestern.edu) while at the 
University of Texas at Austin, but has since been improved upon by several
undergraduate students at Southwestern University in Georgetown, TX, where
Dr. Schrum is currently a professor in the department of Math and Computer Science.
Links to publications and demos further explaining the code are available at 
the official webpage:

http://nn.cs.utexas.edu/?mm-neat
Also on Dr. Schrum's personal webpage:
http://www.southwestern.edu/~schrum2/

More information on NEAT is available in:

K. O. Stanley and R. Miikkulainen, "Evolving Neural Networks Through 
Augmenting Topologies." Evolutionary Computation, 10(2):99-127, 2002.

Information on NSGA-II is available in:

K. Deb, S. Agrawal, A. Pratab, and T. Meyarivan, "A fast elitist nondominated
sorting genetic algorithm for multi-objective optimization: NSGA-II". 
PPSN VI, pp. 849-858, 2000.

A precursor to MM-NEAT is the BREVE Monsters software package, available at:

http://nn.cs.utexas.edu/?brevemonsters

This code was developed primarily to evolve multimodal behavior in Ms. Pac-Man,
and therefore includes (modified) code for the Ms. Pac-Man simulator created for
the Ms. Pac-Man vs. Ghosts Competitions. The original version of this code does not
seem to be available anymore, but a newer version associated with the latest competition
can be downloaded at:

http://www.pacmanvghosts.co.uk/

For further instructions on how to run this code, see TUTORIAL.txt.

For information on the different types of interactive evolution tasks in the code,
see INTERACTIVE_EVOLUTION.txt

FOR MORE INFORMATION CONTACT

schrum2@southwestern.edu