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Atari 2600 game dataset
The dataset used in the paper is the Atari 2600 game dataset, which consists of 4 consecutive 80x80 gray-scale game frames as the input to the network. -
Arcade Learning Environment (ALE) dataset
The dataset used in the paper is the Arcade Learning Environment (ALE) dataset, which consists of 57 classic Atari games. -
Super Mario Bros
The dataset used in the Generative Adversarial Exploration for Reinforcement Learning paper. -
Atari 2600
The dataset used in the paper is the Atari 2600 dataset, which consists of 49 games. The dataset is used to test the Successor Uncertainties algorithm. -
LightZero: A unified benchmark for Monte Carlo Tree Search in general sequent...
The dataset used in the paper is not explicitly described. However, it is mentioned that the authors used Atari environments and board games to evaluate the proposed algorithm. -
OpenAI Gym Atari
The dataset used in the paper is the OpenAI Gym Atari environment. -
Million Base dataset
The Million Base dataset is a large dataset of chess games, containing 2.5 million games. -
StarCraft II with Human Expertise in Subgoals Selection
StarCraft II minigames dataset used for hierarchical reinforcement learning with human expertise in subgoal selection -
Arcade Learning Environment (ALE)
The dataset used in the paper is the Arcade Learning Environment (ALE) dataset, which includes an ATARI 2600 emulator and about 50 games. -
Atari Benchmark
The Atari benchmark is a collection of video game environments with distinctly different dynamics, rewards, and agent embodiments.
