Simulated Robotic Arm Task

该数据集模拟了一个具有两个自由度的机械臂任务，该机械臂在穿过蓝色区域的同时，旨在达到绿色目标。该任务的奖励函数是通过使用随机森林回归从收集的数据中学习得到的。在规模上，对于无模型方法有2500次试验，基于模型的方法有250次试验。任务的类型是顺序目标达到。

This dataset simulates a two-degree-of-freedom robotic arm task, where the robotic arm is required to traverse the blue region while reaching the green target. The reward function for this task is learned from collected data using random forest regression. In terms of scale, there are 2500 trials for model-free methods and 250 trials for model-based methods. The task falls into the category of sequential goal-reaching tasks.