Brax Environment Suite

该数据集是Brax环境套件，包含了一系列用于强化学习的模拟环境，为测试强化学习算法提供了一个框架。该套件包括多种环境，如Humanoid、Hopper、HalfCheetah、Reacher、Fetch以及UR5e，这些环境在强化学习研究中被广泛使用。在不同的环境中，研究者以8个种群大小和1.5亿步的预算进行了测试。这些任务均属于强化学习范畴。

This dataset is the Brax environment suite, which encompasses a series of reinforcement learning simulation environments and provides a standardized framework for evaluating reinforcement learning algorithms. The suite includes multiple widely adopted environments in reinforcement learning research, including Humanoid, Hopper, HalfCheetah, Reacher, Fetch, and UR5e. Researchers conducted experiments across these distinct environments with a population size of 8 and a training step budget of 150 million steps. All these tasks fall within the scope of reinforcement learning.