MM-NEAT Copyright (c) 2014 The University of Texas at Austin 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 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. The code was developed by Jacob Schrum (schrum2@cs.utexas.edu) while at the University of Texas at Austin. Links to publications and demos further explaining the code are available at the official webpage: http://nn.cs.utexas.edu/?mm-neat 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, which can be downloaded in its original form at this address: http://www.pacman-vs-ghosts.net/ For further instructions on how to run this code, see TUTORIAL.txt. FOR MORE INFORMATION CONTACT schrum2@cs.utexas.edu