The AleControl gives Windows C# developers easy access to the Arcade-Learning-Environment (ALE)[1]. ALE is a modification of the Atari-2600 Emulator[2] from the Stella Team that provides access to numerous ATARI games (such as Pong, Space Invaders, etc) for Reinforcement Learning. The games run actions provided by the user and produce their overall game visualizations and game state.
For more information on ALE, please see https://github.com/mgbellemare/Arcade-Learning-Environment
For more information on Stella, please see https://github.com/stella-emu/stella
The AleControl uses the 'atari_win64' source tree which is a fork off the ALE Github tree that has been modified to run as a Windows 64-bit DLL and is licensed under the GNU license.
The 'atari_win64' project uses the Simple DirectMedia Layer (SDL for short) which is a cross-platform library designed to make it easy to write multi-media software such as games and emulators.
The Simple DirectMedia Layer library source code is available from: http://www.libsdl.org, and the SDL library is distributed under the terms of the GNU LGPL License.
The AleControl, written by SignalPop LLC, is a Windows 64-bit COM control that gives any OLE Automation enabled language (C#, Visual Basic, etc.) easy access to the ALE environment via OLE Automation and is licensed under the Apache 2.0 license. An extensive list of ATARI game ROM files is provided by OpenAI on Github at openai/atari-py/atari_roms and are distributed under the GNU GPL License. You can also use Nuget to get the AleControl.
When used in combination with MyCaffe (A complete C# re-write of CAFFE[3]) the AleControl can be used to solve Reinforcement Learning related problems via the MyCaffeTrainerRL control. You can also use Nuget to get MyCaffe.
The SignalPop AI Designer provides a development environment allows you to quickly pull all of these parts together to visually design MyCaffe based models that are both compatible with native CAFFE and support Reinforcement Learning for the Arcade-Learning-Envrionment.
* Visual Studio 2017* Visual Studio 2015
[1] [The Arcade Learning Environment: An Evaluation Platform for General Agents](https://arxiv.org/abs/1207.4708) by Marc G. Bellemare, Yavar Naddaf, Joel Veness and Michael Bowling, 2012-2013. Source code available on GitHub at mgbellemare/Arcade-Learning-Envrionment
[2] [Stella - A multi-platform Atari 2600 VCS emulator](https://stella-emu.github.io/) by Bradford W. Mott, Stephen Anthony and The Stella Team, 1995-2018 Source code available on GitHub at stella-emu/stella
[3] [CAFFE: Convolutional Architecture for Fast Feature Embedding](https://arxiv.org/abs/1408.5093) by Yangqing Jai, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross Girshick, Sergio Guadarrama, and Trevor Darrell, 2014. Source code available on Github at BVLC/caffe