Mujoco 2.0 environments

该数据集包含了在Mujoco 2.0模拟环境中用于训练和评估基于模型的强化学习算法的场景。该数据集被用于比较两种算法——PETS和MBPO在不同Mujoco环境（如倒立摆、半猎豹和推车杆）中的性能表现。这些环境具有连续的状态-动作空间，所涉及的任务是基于模型的强化学习。

This dataset comprises scenarios for training and evaluating model-based reinforcement learning algorithms within the Mujoco 2.0 simulation environment. It is employed to compare the performance of two algorithms, PETS and MBPO, across various Mujoco environments including Inverted Pendulum, HalfCheetah, and CartPole. All these environments feature continuous state-action spaces, and the associated tasks fall under the domain of model-based reinforcement learning.