Gym Benchmarks

该数据集包含了基于Gym的各种基准测试，特别是经典控制、Box2d和Mujoco环境，这些环境被用于评估FAC算法相较于基准算法的性能。这些基准测试涵盖了经典控制、Box2d和Mujoco环境，并用于衡量奖励累积和政策执行的表现。该数据集规模包含九个基准任务，其任务是利用强化学习进行控制策略的合成。

This dataset includes various Gym-based benchmark tests, specifically Classic Control, Box2d and Mujoco environments, which are utilized to evaluate the performance of the FAC algorithm compared to baseline algorithms. These benchmark tests cover Classic Control, Box2d and Mujoco environments, and are used to measure performance related to cumulative reward and policy execution. The dataset comprises nine benchmark tasks, whose purpose is to synthesize control policies through reinforcement learning.