![]() For more details check out the example python-rom-package. ale-import-roms roms/įurthermore, Python packages can expose ROMs for discovery using the special ale-py.roms entry point. You can simply specify a directory as the first argument to this tool and we'll import all supported ROMs by the ALE. First is the command line tool ale-import-roms. The ALE doesn't distribute ROMs but we do provide a couple tools for managing your ROMs. You can now import the ALE in your Python projects with from ale_py import ALEInterface ale = ALEInterface () ROM Management ![]() ![]() Note: Make sure you're using an up to date version of pip or the install may fail. You simply need to install the ale-py package distributed via PyPI: pip install ale-py The ALE currently supports three different interfaces: C++, Python, and OpenAI Gym. Multi-platform code (compiled and tested under macOS, Windows, and several Linux distributions).Automatic extraction of game score and end-of-game signal for more than 100.Emulation core uncoupled from rendering and sound generation modules for fastĮmulation with minimal library dependencies.Object-oriented framework with support to add agents and games.See the Citing section for BibTeX entries. If you use ALE in your research, we ask that you please cite this paper in reference to the environment. This video depicts over 50 games currently supported in the ALE.įor an overview of our goals for the ALE read The Arcade Learning Environment: An Evaluation Platform for General Agents. It is built on top of the Atari 2600 emulator Stella and separates the details of emulation from agent design. The Arcade Learning Environment (ALE) is a simple framework that allows researchers and hobbyists to develop AI agents for Atari 2600 games.
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