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Benchmark data (i.e., DeepMind Control Suite and MuJoCo) for RL.

Benchmark data (i.e., DeepMind Control Suite and MuJoCo) for RL.
All baseline algorithms are running based on the code repository from: ① Spinning Up repository / ② Fujimoto TD3 repository / ③ QingLi Implementation.
Baseline algorithms are listed as below:

Plot results

# eg. Notice: `-l` denotes labels, and `-s` represents smoothing value.
python spinupUtils/plot.py \
    MuJoCo-3M/SpinningUp/DDPG/DDPG-Hopper-v2 \
    MuJoCo-3M/SpinningUp/PPO/PPO-Hopper-v2 \
    MuJoCo-3M/SpinningUp/TD3/TD3-Hopper-v2 \
    MuJoCo-3M/SpinningUp/SAC/SAC-Hopper-v2 \
    --env Hopper-v2 \
    -l DDPG PPO TD3 SAC -s 10

MuJoCo-3M

Including Ant-v2, HalfCheetah-v2, Hopper-v2, Humanoid-v2, Swimmer-v2, Walker2d-v2.

  • Code of baseline algorithms is from Spinning Up repository, the agents are running for 3 million time steps.

  • Code of baseline algorithms is from QingLi Implementation, the agents are running for 3 million time steps.

MuJoCo-1M

Including Ant-v2, HalfCheetah-v2, Hopper-v2, Humanoid-v2, Swimmer-v2, Walker2d-v2.

  • Code of baseline algorithms is from Fujimoto TD3 repository, the agents are running for 1 million time steps by default.

DMControlSuite-3M

Including acrobot-swingup, ball_in_cup-catch, cartpole-swingup, cartpole-swingup_sparse, cartpole-three_poles, cartpole-two_poles, cheetah-run, finger-spin, finger-spin, finger-turn_easy, finger-turn_hard, fish-swim, hopper-hop, hopper-stand, humanoid-run, humanoid-run_pure_state, humanoid-stand, pendulum-swingup, point_mass-easy, point_mass-hard, quadruped-fetch, quadruped-run, quadruped-walk, swimmer-swimmer6, swimmer-swimmer15, walker-run.

  • Code of baseline algorithms is from Spinning Up repository, the agents are running for 3 million time steps.

citation

@misc{QingLi2021continuousbenchmark,
  author = {Qing Li},
  title = {Continuous Control Benchmark of DeepMind Control Suite and MuJoCo},
  year = {2021},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/LQNew/Continuous_Control_Benchmark}}
}