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Temporally Layered Architecture (TLA) for Adaptive, Distributed and Continuou...
The dataset used in the Temporally Layered Architecture (TLA) for adaptive, distributed and continuous control. -
MuJoCo Continuous Control Tasks
The dataset used in the paper is a collection of data from the MuJoCo continuous control tasks. -
Hopper and Half-Cheetah tasks
The dataset used in the paper is a continuous control tasks, specifically the Hopper and Half-Cheetah tasks. -
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. -
Mujoco Benchmarking Continuous Control Tasks
The dataset used in the paper is the Mujoco benchmarking continuous control tasks. -
Mountain Car
The dataset used in the paper is a reinforcement learning dataset, specifically a Markov Decision Process (MDP) with a finite set of states and actions. -
Lunar Lander
The dataset used in this paper is a collection of data points from a lunar lander, which is used to test the proposed APG algorithm for task switching. -
DDPG from Demonstrations
The dataset used in the paper is a set of demonstrations for a robot insertion task, which is a continuous control problem. The demonstrations are collected by a robot... -
Dual Policy Distillation
The dataset used in the paper is a continuous control task dataset. -
LocoMujoco
Motion-capture datasets for robotic continuous control tasks. -
Real-World RL Challenge
The dataset used in the paper is the Real-World RL Challenge dataset. It contains a set of continuous control tasks. -
DeepMind Control Suite and Real-World RL Experiments
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. -
Deterministic Policy Gradients With General State Transitions
The authors used the ComplexPoint-v0, Pendulum-v0, LunarLanderContinuous-v2, Swimmer-v2, HalfCheetah-v2, HumanoidStandup-v2, Humanoid-v2 datasets for experiments. -
DeepMind Control Suite
The DeepMind Control Suite is a collection of 20 robotic manipulation tasks, each with 5 different environments and 5 different robot parameters. The tasks are designed to test... -
Roboschool
The dataset used in the ACE algorithm for continuous control problems. -
OpenAI Gym
The dataset used in the paper is not explicitly described, but it is mentioned that the authors used several continuous control environments from the OpenAI Gym.
