328 datasets found

The dataset used in the paper is the OpenAI Gym dataset, which consists of a set of environments for reinforcement learning.

The dataset used in the paper is the Arcade Learning Environment (ALE) dataset, which consists of 57 classic Atari games.

Interaction Networks: Using a Reinforcement Learner to train other Machine Learning algorithms

The Playground environment is a continuous 2D world. In each episode, N = 3 objects are uniformly sampled from a set of 32 different object types (e.g. dog, cactus, sofa, water,...

To overcome the sim-to-real gap in reinforcement learning (RL), learned policies must maintain robustness against environmental uncertainties. While robust RL has been widely...

The dataset used in the paper is a set of real-world robot learning tasks, including Create-Reacher, UR5-VisualReacher, Vector-ChargerDetector, and Franka-VisualReacher.

The 2D Grid World environment with various items and consequences

The Cartpole-v1 environment is used to evaluate the performance of Federated Reinforcement Distillation (FRD) framework.

MuZero, a model-based reinforcement learning algorithm that uses a value equivalent dynamics model.

The Google Research Football environment is a reinforcement learning experimental platform focused on training agents to play football.

The dataset is used for training a neural network consisting of 2 blocks of convolutional layers followed by max pooling layers and an LSTM block.

The authors used the ComplexPoint-v0, Pendulum-v0, LunarLanderContinuous-v2, Swimmer-v2, HalfCheetah-v2, HumanoidStandup-v2, Humanoid-v2 datasets for experiments.

The dataset used in the Generative Adversarial Exploration for Reinforcement Learning paper.

The dataset used in the Generative Adversarial Exploration for Reinforcement Learning paper.

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.

The dataset used in the paper is a set of environments for reinforcement learning, including CartPole, Pendulum, and LunarLander.

The dataset used for training the Dreamer model.

The MineCLIP dataset is a large-scale dataset of Minecraft demonstrations.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used a combination of reinforcement learning and generative models to solve...

The dataset is used to train and test the autohedger model.