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Multi-Agent Environment
The dataset used in the paper is a multi-agent environment where agents learn to coordinate their actions to achieve a common goal. The dataset is used to evaluate the proposed... -
Using Reinforcement Learning for the Three-Dimensional Loading Capacitated Ve...
The 3L-CVRP is a long-standing problem in the operations research literature. However, these existing approaches have two shortcomings. First, existing approaches are based on... -
Reinforcement learning for pursuit and evasion of microswimmers at low Reynol...
The dataset is used to study the pursuit and evasion of microswimmers at low Reynolds number. -
Spacecraft Inspection Task
The dataset used in this paper for the spacecraft inspection task, which involves training a neural network controller (NNC) and run time assurance (RTA) algorithms. -
HalfCheetah and Walker2d
The dataset used in the paper is the HalfCheetah and Walker2d environments from the D4RL dataset. -
Crop Yield Optimization
A plant simulation environment with an OpenAI Gym interface, used to optimize crop yield using reinforcement learning algorithms. -
MineRL Diamond
The MineRL Diamond dataset is a large-scale dataset of Minecraft demonstrations, focusing on the development of sample-efficient reinforcement learning algorithms for mining... -
Mario AI Benchmark
The Mario AI benchmark dataset is used to evaluate the proposed approach to translate a policy trained by a Deep RL algorithm into a set of rules. -
OpenAI Gym and Roboschool
The dataset used in the paper is not explicitly described, but it is mentioned that the authors used OpenAI Gym and Roboschool environments. -
Leveraging Reward Gradients For Reinforcement Learning in Differentiable Phys...
A novel algorithm, Cross Entropy Analytic Policy Gradients (CE-APG), that is able to leverage analytic gradients to outperform state of the art deep reinforcement learning on a... -
Exploration Metrics for Reinforcement Learning
The dataset used in the paper is a set of data generated from four different types of distributions: uniform, truncated normal, bi-modal truncated normal growing scale, and... -
MountainCar environment
The authors used the MountainCar environment for reinforcement learning experiments. -
Autonomous Reinforcement Learning of Multiple Interrelated Tasks
The dataset used in the paper is a simulated robotic scenario involving multiple interrelated tasks. -
Aaren: Efficient Attention for Sequence Modeling
The dataset used in the paper is a collection of 38 datasets spread across four popular sequential problem settings: reinforcement learning, event forecasting, time series... -
Object Collection Game
The object collection game is a simple 2D video game that requires the agent to collect objects that move from the top of the screen to the bottom. -
ProcGen environments
The dataset used in the paper is a procedurally-generated (PCG) environment, specifically the MiniGrid and ProcGen environments. -
MiniGrid and ProcGen environments
The dataset used in the paper is a procedurally-generated (PCG) environment, specifically the MiniGrid and ProcGen environments. -
Minigrid environment
The dataset used in the paper is the Minigrid environment, which is a 3D grid world with a goal at the bottom-right corner. The agent learns to navigate to the goal using human...
