HyperNEAT v4.0 C++ / Mod Anthony Wertz awertz@knights.ucf.edu License and the original usage and installation information is repeated below. The HyperNEAT source had not been touched in a while so this fork is an attempt to make it build fine on more recent systems (Ubuntu 12.04 for example). This should bring it up to date. In the future, this should turn into an Ubuntu package to be less cludgy but for now here are some minor adjustments. If you are using Ubuntu 12.04, you can find a script 'get_hyperneat' in the 'external' directory of my repository here: https://github.com/anthonytw/neat-deforms Hopefully you find this useful. Happy hacking. :) ---------------------- ORIGINAL README BELOW ---------------------------- HyperNEAT v4.0 C++, By Jason Gauci http://ucfpawn.homelinux.com/joomla/ jgauci@cs.ucf.edu Documentation for this package is included in this README file. ------------- 1. LICENSE ------------- This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License version 2 as published by the Free Software Foundation (LGPL may be granted upon request). This program is distributed in the hope that it will be useful, but without any warranty; without even the implied warranty of merchantability or fitness for a particular purpose. See the GNU General Public License for more details. --------------------- 2. USAGE and SUPPORT --------------------- We hope that this software will be a useful starting point for your own explorations in interactive evolution with NEAT. The software is provided as is; however, we will do our best to maintain it and accommodate suggestions. If you want to be notified of future releases of the software or have questions, comments, bug reports or suggestions, send an email to jgauci@cs.ucf.edu Alternatively, you may post your questions on the NEAT Users Group at : http://tech.groups.yahoo.com/group/neat/. The following explains how to use HyperNEAT. For information on compiling HyperNEAT, please see the section on compiling below. INTRO ----- HyperNEAT is an extension of NEAT (NeuroEvolution of Augmenting Topologies) that evolves CPPNs (Compositional Pattern Producing Networks) that encode large-scale neural network connectivity patterns. A complete explanation of HyperNEAT is available here: @InProceedings{gauci:aaai08, author = "Jason Gauci and Kenneth O. Stanley", title = "A Case Study on the Critical Role of Geometric Regularity in Machine Learning", booktitle = "Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence (AAAI-2008).", year = 2008, publisher = "AAAI Press", address = "Menlo Park, CA", site = "Chicago", url = "http://eplex.cs.ucf.edu/publications.html#gauci.aaai08", } @InProceedings{gauci:gecco07, author = "Jason Gauci and Kenneth O. Stanley", title = "Generating Large-Scale Neural Networks Through Discovering Geo metric Regularities", booktitle = "Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2007)", year = 2007, publisher = "ACM Press", address = "New York, NY", site = "London", url = "http://eplex.cs.ucf.edu/index.php?option=com_content&task=view&id=14&Itemid=28#gauci.gecco07", } The version of HyperNEAT distributed in this package executed the experiments in the above papers. For more information, please visit the EPlex website at: http://eplex.cs.ucf.edu/ or see more of our publications on HyperNEAT and CPPNs at: http://eplex.cs.ucf.edu/publications.html COMMAND LINE ------------ To use the command line interface, simply pass the data file and the output file as parameters to the HyperNEAT executable, and it will process the data file and put the resulting population as an XML file in the output file location. GUI --- To load an experiment, go to file->load_experiment and then select the .dat file that corresponds to the experiment you would like to load. When the experiment is loaded, go to file->run_experiment to begin the experiment. In the console, you can see the results for each generation. If you wish to pause the experiment, go to file->pause_experiment. This command will finish the current generation and then halt the experiment. You can continue by going to file->continue_experiment. At the moment, the restart_experiment function has not been implemented and you can't load another experiment without first closing the program (although you may "continue experiment" after you have paused). It is possible to view an individual interactively by choosing the individual you want from the spinners and then clicking "view". This brings up a separate window where you can interact with the individual (if the experiment supports it) and you can also see the CPPN that created the individual. Some experiments contain a post-hoc analysis that does a more complete test of an individual. This analysis can be achieved by clicking the "Analyze" button and the results are typically displayed in the console. -------------- 3. EXPERIMENTS -------------- FIND CLUSTER EXPERIMENT ----------------------- This is the experiment presented in the GECCO 2007 paper (see above). The goal of the experiment is for the network to generate the highest amount of activation at the center of the larger square, regardless of the positions. While in the view panel, a number of functions are possible: To position a square, click on the substrate (the grid). It will place one square and then the other. To view the connectivity, right-click. As you move the mouse across the grid, each square in the grid now represents the connection going from the grid square under your mouse to that location. A cross-hatch pattern represents a negative weight. You can return to the input layer by right-clicking again. To view the substrate output, middle-click. The resulting grid represents the output plane of the state space sandwich. The darker colors represent a higher activation level, and a cross-hatch pattern represents a negative level of activation. you can return to the input layer by middle-clicking. To save a series of images of your state at several resolutions, click on "Save Images" at the top. *NOTE* This takes a very long time! To increase/decrease the resolution of the substrate, click the appropriate wording on the screen. *NOTE* This also takes a very long time! FIND CLUSTER NO GEOM EXPERIMENT ------------------------------- This is the "Find Cluster Experiment" but using P-NEAT (perceptron NEAT). This takes a very long time because it's trying to use NEAT on a 14641-link network. FIND POINT EXPERIMENT --------------------- This was the precursor to the FindClusterExperiment. It looks for a point on the input substrate and tries to put a similar point on the output substrate. I'm not sure if it still works. TIC TAC TOE EXPERIMENT ---------------------- This was designed as a proof of concept that we could solve Tic Tac Toe. It tries to set an output value high when there is a tic tac toe (i.e., someone has won). TIC TAC TOE GAME EXPERIMENT ---------------------- This is a Tic Tac Toe implementation in HyperNEAT. It can consistently produce a perfect tic tac toe player. During training, an individual is exposed to every possible tic tac toe game. Even so, it runs fairly quickly. CHECKERS EXPERIMENT ------------------- This is the HyperNEAT implementation of Checkers, as discussed in the AAAI 08 paper (see above). The goal of the experiment is to defeat the Simplech heuristic in checkers at a ply depth of 4. If you view an individual, you can play a game of checkers against any individual at any generation you specify. When you see "Black's turn. Click to see black's move", simply click on the board and it will show you the move that the computer made. When you see "Move from?", click on the white piece that you would like to move, and when you see "Move to?", click on the destination. If you would like to jump a piece or several pieces, click on the destination after all the jumps. If the move was valid, you will see the board change and then you can click to see HyperNEAT's response. If the move wasn't valid, you will be asked "Move from?" and you must pick a valid move. *NOTE*: There is nothing in the fitness function to prevent HyperNEAT from deciding that a board evaluation of 0.9999 is completely winning for white and 0.99999999 is completely winning for black. As a result, all of the board evaluation functions will be in the range [0.9999, 0.99999999]. As a result of this, the evaluation process could become dependent on the specific architecture of your computer and floating point implementation of your compiler. I have found that changing this line: typedef float CheckersNEATDatatype; to: typedef double CheckersNEATDatatype; allows you to evaluate a run from one architecture on another architecture without losing performance. I have only tested this on a few runs. Ideally, if you want to see the real performance of an individual, the best thing is to evolve your own player on your machine. CHECKERS ORIGINAL FOGEL EXPERIMENT ---------------------------------- This is called NEAT-EI in the paper. It is an implementation of the NEAT Checkers player as inspired by Charapella & Fogel (see AAAI 08 paper above). This player does not use HyperNEAT, but uses a direct encoding with engineered inputs. *NOTE*: Please see *NOTE* above, as it applies to this method as well. -------------- 4. RESULTS -------------- A number of completed runs have been placed in the "out/Results/" folder. To load one of these runs, select "file->load_population" from the menu bar. -------------- 5. COMPILING -------------- DEPENDENCIES -------------- HyperNEAT depends on the TinyXMLDLL Library version 2.0 (http://ucfpawn.homelinux.com/joomla/tinyxmldll/3.html), JG Template Library (http://sourceforge.net/projects/jgtl/), Boost c++ libraries (http://www.boost.org/) and WxWidgets *Only if building in GUI mode* (http://www.wxwidgets.org/). For information on how to build & install those libraries, please see their respective websites. HyperNEAT uses cmake as it's build system, and requires cmake 2.6 or later. BUILD INSTRUCTIONS: --------------- UNIX/LINUX/CYGWIN/MACOSX: Inside the HyperNEAT/build directory, create two subdirectories, one for debug and one for release: mkdir build/cygwin_debug mkdir build/cygwin_release Now, run cmake on each of those directories with the -i option, and put the appropriate configuration (debug for *_debug, release for *_release): cmake -i ../../ The USE_GUI setting can be set to turn on/off the GUI. If the GUI is disabled, the code does not depend on WxWidgets. Now, just run "make" on the build/*/ directories and the dlls & libraries should be created in the out/ folder WINDOWS: Inside the build directory, create a subdirectory: build/msvc8 (or whatever version you have) Now, run cmake on that subdirectory. The USE_GUI setting can be set to turn on/off the GUI. If the GUI is disabled, the code does not depend on WxWidgets. Then, open the project and build a debug and release version. If the compiler is unable to find certain header files, that probably means that you need to correctly set the CMake build variables that have to do with the location of include files for the dependencies. If the linker is unable to find certain library files, that means that you either need to fix the CMake build variables for libraries, or that the names of the libraries have changed for some reason. -------------- 6. FORUM -------------- We are available to answer questions at the NEAT Users Group: http://tech.groups.yahoo.com/group/neat/