15 Commits

Author SHA1 Message Date
ChenDRAG
929508ba77
Update experiment details of MuJoCo benchmark (#779)
Update the downloading url of the training logs and saved checkpoints
for MuJoCo tasks.
2022-11-26 10:18:22 -08:00
Juno T
d42a5fb354
Hindsight Experience Replay as a replay buffer (#753)
## implementation
I implemented HER solely as a replay buffer. It is done by temporarily
directly re-writing transitions storage (`self._meta`) during the
`sample_indices()` call. The original transitions are cached and will be
restored at the beginning of the next sampling or when other methods is
called. This will make sure that. for example, n-step return calculation
can be done without altering the policy.

There is also a problem with the original indices sampling. The sampled
indices are not guaranteed to be from different episodes. So I decided
to perform re-writing based on the episode. This guarantees that the
sampled transitions from the same episode will have the same re-written
goal. This also make the re-writing ratio calculation slightly differ
from the paper, but it won't be too different if there are many episodes
in the buffer.

In the current commit, HER replay buffer only support 'future' strategy
and online sampling. This is the best of HER in term of performance and
memory efficiency.

I also add a few more convenient replay buffers
(`HERVectorReplayBuffer`, `HERReplayBufferManager`), test env
(`MyGoalEnv`), gym wrapper (`TruncatedAsTerminated`), unit tests, and a
simple example (examples/offline/fetch_her_ddpg.py).

## verification
I have added unit tests for almost everything I have implemented.
HER replay buffer was also tested using DDPG on [`FetchReach-v3`
env](https://github.com/Farama-Foundation/Gymnasium-Robotics). I used
default DDPG parameters from mujoco example and didn't tune anything
further to get this good result! (train script:
examples/offline/fetch_her_ddpg.py).


![Screen Shot 2022-10-02 at 19 22
53](https://user-images.githubusercontent.com/42699114/193454066-0dd0c65c-fd5f-4587-8912-b441d39de88a.png)
2022-10-30 16:54:54 -07:00
Jiayi Weng
2a7c151738
Add vecenv wrappers for obs_norm to support running mujoco experiment with envpool (#628)
- add VectorEnvWrapper and VectorEnvNormObs
- obs_rms store in policy save/load
- align mujoco scripts with atari: obs_norm, envpool, wandb and README
2022-05-05 19:55:15 +08:00
ChenDRAG
5c9afe72f3
Update Mujoco Bemchmark's webpage (#606) 2022-04-24 01:11:33 +08:00
ChenDRAG
bbc3c3e32d
Add numerical analysis tool and interactive plot (#341)
Co-authored-by: Trinkle23897 <trinkle23897@gmail.com>
2021-04-22 12:49:54 +08:00
ChenDRAG
844d7703c3
NPG Mujoco benchmark release (#347) 2021-04-21 16:31:20 +08:00
ChenDRAG
a57503c0aa
TRPO benchmark release (#340) 2021-04-19 17:05:06 +08:00
ChenDRAG
333b8fbd66
add plotter (#335)
Co-authored-by: Trinkle23897 <trinkle23897@gmail.com>
2021-04-14 14:06:36 +08:00
ChenDRAG
6426a39796
ppo benchmark (#330) 2021-03-30 11:50:35 +08:00
ChenDRAG
1730a9008a
A2C benchmark for mujoco (#325) 2021-03-28 13:12:43 +08:00
ChenDRAG
3ac67d9974
refactor A2C/PPO, change behavior of value normalization (#321) 2021-03-25 10:12:39 +08:00
ChenDRAG
47c77899d5
Add REINFORCE benchmark for mujoco (#320) 2021-03-24 19:59:53 +08:00
ChenDRAG
e605bdea94
MuJoCo Benchmark - DDPG, TD3, SAC (#305)
Releasing Tianshou's SOTA benchmark of 9 out of 13 environments from the MuJoCo Gym task suite.
2021-03-07 19:21:02 +08:00
Trinkle23897
cd481423dc sac mujoco result (#246) 2020-11-09 16:43:55 +08:00
youkaichao
a9f9940d17
code refactor for venv (#179)
- Refacor code to remove duplicate code

- Enable async simulation for all vector envs

- Remove `collector.close` and rename `VectorEnv` to `DummyVectorEnv`

The abstraction of vector env changed.

Prior to this pr, each vector env is almost independent.

After this pr, each env is wrapped into a worker, and vector envs differ with their worker type. In fact, users can just use `BaseVectorEnv` with different workers, I keep `SubprocVectorEnv`, `ShmemVectorEnv` for backward compatibility.

Co-authored-by: n+e <463003665@qq.com>
Co-authored-by: magicly <magicly007@gmail.com>
2020-08-19 15:00:24 +08:00