Arcade Learning Environment

Principal Investigator
Michael Bowling

Atari 2600 Platform for General Artificial Intelligence Development

The Arcade Learning Environment (ALE) is a software framework designed to facilitate the development and testing of general AI agents. ALE was created as both a challenge problem for AI researchers and a method for developing and evaluating innovations and technologies.

Historically, many AI advancements have been developed and tested through games (e.g. CheckersChessPoker and, most recently, Go), which offer controlled, well-understood environments with easily defined measures for success. Games also give researchers a concrete and relatable way to demonstrate artificial intelligence to a broad audience.

The Arcade Learning Environment, powered by the Stella Atari Emulator, provides an interface to hundreds of Atari 2600 games. These diverse game environments are complex enough to be challenging for an AI agent to solve yet simple enough to enable progress.

ALE is available to researchers and hobbyists alike with Atari now being used by groups like DeepMind to develop and test their deep reinforcement learning methodologies.

See Also

The Arcade Learning Environment: An Evaluation Platform for General Agents” published in the Journal of Artificial Intelligence Research