328 datasets found

A Deep Reinforcement Learning framework for task arrangement in crowdsourcing platforms.

The dataset used in the paper is the BabyAI environment 'BabyAI-PickUpDist-v0' with a one-pickup-per-episode wrapper.

The CT-graph and Minigrid environments are used to evaluate lifelong reinforcement learning approaches.

A dataset for robotic manipulation tasks, including ChestPush, ChestPickAndPlace, and BlockStack.

A dataset for multi-step sparse reward tasks, including gridworld tasks and robotic manipulation tasks.

The Atari 2600 domain dataset, used for training and testing reinforcement learning algorithms.

The Sungka dataset is a two-player turn-based board game where each player takes turns moving stones to collect as many stones as possible.

The dataset used in the paper is the Real-World RL Challenge dataset. It contains a set of continuous control tasks.

The dataset used in the paper is the Go dataset. It contains a set of Go games.

The Atari dataset is a collection of 55 Atari games, each with its own set of rules and objectives.

The dataset used in the paper is the DeepMind Control Suite and Real-World RL Experiments. It contains a set of continuous control tasks based on MuJoCo.

The dataset used in this paper is the CartPole and Blackjack environments from OpenAI Gym.

The dataset used in the paper is a collection of experiences sampled from a replay buffer, used to train and evaluate the proposed Multi-step DDPG (MDDPG) and Mixed Multi-step...

An environment where the agent must intercept a ball thrown towards it before it crosses the goal line.

An environment where the agent must hover over a target using pulses in two dimensions.

A visual version of the CartPole environment from OpenAI Gym.

A custom visual environment for reinforcement learning with rendering capabilities.

The dataset used in the paper is a collection of instruction sets and states for the Contra game, used to train a language model and a reinforcement learning policy.

The dataset used in the paper is a collection of instruction sets and states for the Contra game, used to train a language model and a reinforcement learning policy.

The dataset used in the paper is a collection of instruction sets and states for the Contra game, used to train a language model and a reinforcement learning policy.