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Tianshou/examples/box2d
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n+e 710966eda7
change API of train_fn and test_fn (#229) 
train_fn(epoch) -> train_fn(epoch, num_env_step)
test_fn(epoch) -> test_fn(epoch, num_env_step)
2020-09-26 16:35:37 +08:00
..
results/sac
SAC implementation update (#212)
2020-09-12 08:44:50 +08:00
acrobot_dualdqn.py
change API of train_fn and test_fn (#229)
2020-09-26 16:35:37 +08:00
bipedal_hardcore_sac.py
change API of train_fn and test_fn (#229)
2020-09-26 16:35:37 +08:00
lunarlander_dqn.py
change API of train_fn and test_fn (#229)
2020-09-26 16:35:37 +08:00
mcc_sac.py
change API of train_fn and test_fn (#229)
2020-09-26 16:35:37 +08:00
README.md
SAC implementation update (#212)
2020-09-12 08:44:50 +08:00

README.md

Bipedal-Hardcore-SAC

  • Our default choice: remove the done flag penalty, will soon converge to ~270 reward within 100 epochs (10M env steps, 3~4 hours, see the image below)
  • If the done penalty is not removed, it converges much slower than before, about 200 epochs (20M env steps) to reach the same performance (~200 reward)