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The project is an Open Source implementation of a cellular automata written in Java. In the Java version, each cell is represented by a two dimensional array. The current or last update date is displayed. Langton's Ant can run on all Java-enabled machines and operating systems (Linux, Windows, MacOS). Licence: Langton's Ant is released under the GNU GPL v2.0 licence. Langton's Ant is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 2 of the License, or (at your option) any later version. Langton's Ant 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. The copyright and license notices above must be included in any distributions. For more information on the GNU GPL, see More information on Langton's Ant is available at The latest version of Langton's Ant is available on Github at Latest version: 02-11-2018 - Version 1.4.0: - Fixed some bugs in the analysis. - Code cleanup. - Now it is possible to analyze the state of the animation just by pressing the space bar. - Added a button in the menu that allows to analyze the state of the animation. - Version 1.4.0 of Langton's Ant is now available in JAR format. 15-07-2017 - Version 1.3.0: - Improved the display of the time. - Fixed the crash that could occur when using version 1.3.0 of Langton's Ant. - Code cleanup. 17-03-2017 - Version 1.2.0: - Improved the initialization of the variables used in the engine. - Several bugs in the core engine are fixed. - Added a setting to specify the size of the window that will be used in the simulations. - Now there is an option to specify the number of generations to analyze. - Updated the copyright and license. 23-12-2016 - Version 1.1.0: - Major code refactoring. - The previous version was a beta version that had a few bugs. - Fixed the bug in the initialization of the variables that was preventing some patterns to appear.
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