Atari-5: Distilling the Arcade Learning Environment down to Five Games

2022-10-05 · Matthew Aitchison, Penny Sweetser, Marcus Hutter

The Arcade Learning Environment (ALE) has become an essential benchmark for assessing the performance of reinforcement learning algorithms. However, the computational cost of generating results on the entire 57-game dataset limits ALE's use and makes the reproducibility of many results infeasible. We propose a novel solution to this problem in the form of a principled methodology for selecting small but representative subsets of environments within a benchmark suite. We applied our method to identify a subset of five ALE games, called Atari-5, which produces 57-game median score estimates within 10% of their true values. Extending the subset to 10-games recovers 80% of the variance for log-scores for all games within the 57-game set. We show this level of compression is possible due to a high degree of correlation between many of the games in ALE.

📄 PDF Abstract BibTeX arXiv:2210.02019

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maitchison/atari-5 공식 구현

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Atari Games

CALE: Continuous Arcade Learning Environment

2024-10-31 · Jesse Farebrother, Pablo Samuel Castro

We introduce the Continuous Arcade Learning Environment (CALE), an extension of the well-known Arcade Learning Environment (ALE) [Bellemare et al., 2013]. The CALE uses the same underlying emulator of the Atari 2600 gami…

Atari Games Benchmarking continuous-control Continuous Control

Multiplayer Support for the Arcade Learning Environment

2020-09-20 · Justin K. Terry, Benjamin Black, Luis Santos

The Arcade Learning Environment ("ALE") is a widely used library in the reinforcement learning community that allows easy programmatic interfacing with Atari 2600 games, via the Stella emulator. We introduce a publicly a…

Atari Games reinforcement-learning Reinforcement Learning (RL)

Octax: Accelerated CHIP-8 Arcade Environments for Reinforcement Learning in JAX

2025-10-02 · Waris Radji, Thomas Michel, Hector Piteau arxiv

Reinforcement learning (RL) research requires diverse, challenging environments that are both tractable and scalable. While modern video games may offer rich dynamics, they are computationally expensive and poorly suited…

Reinforcement Learning Atari Games

Playing Atari with Deep Reinforcement Learning

2013-12-19 · Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves 외

We present the first deep learning model to successfully learn control policies directly from high-dimensional sensory input using reinforcement learning. The model is a convolutional neural network, trained with a varia…

Atari Games Deep Reinforcement Learning Multi-Goal Reinforcement Learning Q-Learning+2

MinAtar: An Atari-Inspired Testbed for Thorough and Reproducible Reinforcement Learning Experiments

2019-03-07 · Kenny Young, Tian Tian

The Arcade Learning Environment (ALE) is a popular platform for evaluating reinforcement learning agents. Much of the appeal comes from the fact that Atari games demonstrate aspects of competency we expect from an intell…

Atari Games reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)+1