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Alchemy: A structured task distribution for meta-reinforcement learning
The Alchemy benchmark is a meta-learning environment rich enough to contain interesting abstractions, yet simple enough to make ne-grained analysis tractable. -
Mujoco control tasks
The authors used the Mujoco control tasks, including Ant-v2, HalfCheetah-v2, Hopper-v2, and Walker2d-v2. -
DCG-MAP-Elites-AI
The dataset used in this paper is a set of seven continuous control locomotion tasks implemented in Brax, derived from standard RL benchmarks. -
Pong and Breakout
The dataset used in the paper is a collection of tasks from OpenAI Gym, specifically Pong and Breakout. -
Sym-Q: Adaptive Symbolic Regression via Sequential Decision-Making
Symbolic regression holds great potential for uncovering underlying mathematical and physical relationships from empirical data. The authors introduce Symbolic Q-network... -
Multiple-confounded-Mujoco-Envs
The dataset used in the paper is a collection of environments with multiple confounders, including mass, length, damping, and a crippled leg. The dataset is used to evaluate the... -
HalfCheetah-v3
The dataset used in the paper is a modified version of the HalfCheetah-v3 environment from the OpenAI gym. -
FrozenLake-v0
The dataset used in the paper is a modified version of the FrozenLake-v0 environment from the OpenAI gym. -
PPO Cartpole Task
PPO Cartpole Task -
Euler Equations Dataset
The dataset used in the paper for testing the performance of the trained policy on the Euler equations. -
Backpropagation Through Time and Space
The dataset used in the paper for training a recurrent spatio-temporal network for hyperbolic conservation laws. -
Traffic Light Control Dataset
The traffic light control dataset is used to evaluate the performance of reinforcement learning models in traffic light control. -
HERON: Hierarchical Preference-based Reinforcement Learning
The dataset used in the paper is not explicitly described, but it is mentioned that the authors used a hierarchical reward design framework to train policies in various... -
Four Rooms domain
The Four Rooms domain is a classic reinforcement learning environment where an agent must navigate a grid world to reach one of four goals. -
Wield: Systematic Reinforcement Learning With Progressive Randomization
Wield is a system for systematic task design and evaluation in applied RL. It provides a set of reusable software primitives to decouple system interface and RL representation... -
Simulated Self-Driving Car Environment
The dataset used in the paper is a simulated self-driving car environment, a mountain car environment, and a robotic environment. -
Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Le...
The dataset used in the paper is a collection of expert demonstrations for various tasks, including robotic manipulation, maze navigation, and Atari games. -
Diagnosing Bottlenecks in Deep Q-Learning Algorithms
The dataset used in the paper is a collection of expert demonstrations for various tasks, including robotic manipulation, maze navigation, and Atari games.
