mlsanityData to 14 Oct 2026

An Oracle and Observations for the OpenAI Gym / ALE Freeway Environment

arXiv 2109.01220 ↗First posted 2 Sep 2021cs.AIcited by 0

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Abstract (arXiv)

The OpenAI Gym project contains hundreds of control problems whose goal is to provide a testbed for reinforcement learning algorithms. One such problem is Freeway-ram-v0, where the observations presented to the agent are 128 bytes of RAM. While the goals of the project are for non-expert AI agents to solve the control problems with general training, in this work, we seek to learn more about the problem, so that we can better evaluate solutions. In particular, we develop on oracle to play the game, so that we may have baselines for success. We present details of the oracle, plus optimal game-playing situations that can be used for training and testing AI agents.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 4 references that are in the map. First posted on arXiv 2 Sep 2021.

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References · 2

  1. 2017Rainbow: Combining Improvements in Deep Reinforcement Learningcited by 786
  2. 2017Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agentscited by 269

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