4 Commits

Author SHA1 Message Date
Jialu Zhu
a511cb4779
Add offline trainer and discrete BCQ algorithm (#263)
The result needs to be tuned after `done` issue fixed.

Co-authored-by: n+e <trinkle23897@gmail.com>
2021-01-20 18:13:04 +08:00
wizardsheng
c6f2648e87
Add C51 algorithm (#266)
This is the PR for C51algorithm: https://arxiv.org/abs/1707.06887

1. add C51 policy in tianshou/policy/modelfree/c51.py.
2. add C51 net in tianshou/utils/net/discrete.py.
3. add C51 atari example in examples/atari/atari_c51.py.
4. add C51 statement in tianshou/policy/__init__.py.
5. add C51 test in test/discrete/test_c51.py.
6. add C51 atari results in examples/atari/results/c51/.

By running "python3 atari_c51.py --task "PongNoFrameskip-v4" --batch-size 64", get  best_result': '20.50 ± 0.50', in epoch 9.

By running "python3 atari_c51.py --task "BreakoutNoFrameskip-v4" --n-step 1 --epoch 40", get best_reward: 407.400000 ± 31.155096 in epoch 39.
2021-01-06 10:17:45 +08:00
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
yingchengyang
5b49192a48
DQN Atari examples (#187)
This PR aims to provide the script of Atari DQN setting:
- A speedrun of PongNoFrameskip-v4 (finished, about half an hour in i7-8750 + GTX1060 with 1M environment steps)
- A general script for all atari game
Since we use multiple env for simulation, the result is slightly different from the original paper, but consider to be acceptable.

It also adds another parameter save_only_last_obs for replay buffer in order to save the memory.

Co-authored-by: Trinkle23897 <463003665@qq.com>
2020-08-30 05:48:09 +08:00