328 datasets found

Two real-world datasets provided by Cainiao Network, each containing parcel data and constraints configuration data.

The online parcel assignment problem, which is aimed at assigning each incoming parcel to a candidate route for delivery, in order to minimize the total cost under consideration...

The dataset used in the experiments is the Fetch environment in OpenAI Gym.

ACED constructs a curriculum by sampling states from expert demonstration trajectories as initializations for each training episode, where the samples initially come from near...

The dataset used in the paper is a set of data collected from the OpenAI Gym Reacher environment.

The dataset used in the paper is a set of motor babbling data, which is used to initialize the dynamics model and to optimize the control policies.

A synthetic dataset generated using Google Research Football Environment for training and testing the proposed tracking method.

OmniSafe is a comprehensive infrastructural framework designed to accelerate Safe Reinforcement Learning research.

The dataset is used to train the Make-An-Agent model, a novel policy parameter generator that leverages the power of conditional diffusion models for behavior-to-policy generation.

The dataset is used to train the Make-An-Agent model, a novel policy parameter generator that leverages the power of conditional diffusion models for behavior-to-policy generation.

The dataset is used to train the Make-An-Agent model, a novel policy parameter generator that leverages the power of conditional diffusion models for behavior-to-policy generation.

The dataset used in this paper is a reinforcement learning benchmark problem, specifically the Bipedal Walker, Acrobot, and Continuous Lunar Lander tasks.

The dataset used in the paper is a set of environments for reinforcement learning, including movie recommendations, educational activities sequencing, and HIV treatment.

The BRIDGE dataset is a collection of 155 deterministic MDPs, each with a horizon of 100 time steps. The dataset is used to evaluate the performance of reinforcement learning...

The dataset used in this paper is the DeepMind Control Suite and PyBullet Environments.

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 a Visual Grid World Environment and the TextWorld domain.

The archive A contains policies parameterized by deep neural networks and trained via a state of the art QD-RL method PPGA.

Quality Diversity (QD) is an emerging field in which collections of high performing, behaviorally diverse solutions are trained. The foundational method, Map Elites, maintains...

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...