44 datasets found

The dataset used in the paper is a collection of tic-tac-toe games, where each game is represented as a 9-qubit encoding. The games are encoded using Pauli-X rotations on...

A large-scale dataset of No Press Diplomacy games, containing more than 150,000 human games.

The dataset is used to evaluate agents for the Hanabi card game, a cooperative card game with imperfect information.

The dataset used for the game 'Catch' task, consisting of 28x28 binary pixel images.

The dataset used for training the SAI agent, containing 7x7 Go games with multiple komi values.

The dataset used in the paper is a collection of 6 publicly available datasets from the UCI Machine Learning repository.

The dataset used in the paper is a multi-agent reinforcement learning dataset, where agents learn to coordinate their actions to achieve a common goal.

The Reconnaissance Blind TicTacToe (RBT) dataset is a variation of the Reconnaissance Blind Chess (RBC) challenge. It is a game of TicTacToe where the agent cannot see the moves...

The MineRL-v0 dataset contains human demonstration data for tasks in Minecraft.

The MineRL BASALT competition dataset contains human demonstration data for four tasks in Minecraft.

The dataset used in this work is the Breakout, SeaQuest, Space Invaders, and Qbert environments.

The dataset used in this work is the Atari environment in OpenAI Gym, created by the Arcade Learning Environment (ALE).

The Arcade Learning Environment (ALE) is a lasting and indispensable element of the RL researcher’s toolbox. It is also the focus of our work. Since its inception, hundreds of...

The dataset used in the paper is not explicitly described, but it is mentioned that the authors conducted experiments on several representative tasks from the OpenAI Gym and...

Pommerman is a 2-vs-2 game environment introduced in 2018, and is a modified version of the popular game 'Bomberman'. It is a good testbed for RL, because the environment...

DMLab-30 is a benchmark for multitask reinforcement learning in partially observable environments.

The Arcade Learning Environment

The dataset used in this paper is the Car Racing game dataset, which consists of pixel frames of a car racing game.

The dataset used in this paper is the OpenAI Gym Environment dataset, which consists of various games and environments.

The dataset used in this paper is the Atari 2600 games dataset, which consists of 50 Atari 2600 games.