hilanzy / moss Goto Github PK

1.Refine hyper parameters entropy_coef for Seaquest-v5 in impala.(0.5 is best for now)

2.Fix bugs for local run.

Fix fake behavior_values in PPOLearner._loss to supports value clip operation.

1. code format.
2. torso inputs refactor.
3. action spec refine.
4. reconstruct the directory structure of the network.

Fix data format for image feature to supports NHWC and NCHW.

Add experiment api to make moss more easy to run.

Supplement and improve the doc annotations in Moss.

Refactor input feature and output action networks to make them composable.

Rename VectorActor to make it more suitable for its function.

Add gradient clip trick.
Trick following this blog https://zhuanlan.zhihu.com/p/512327050 (Trick 7).

Add ResizeObservation wrapper for pettingzoo, and add two arguments height and width for PettingZooEnv to set shape of image observation.

Update version to 0.0.3

• Refine FeatureSet process.
• Refine network input feature.
• Fix torso inputs concatenate axis.

Supports sampling data async in venv(now just for envpool).

Refactor the Moss environment to make it more generic, allowing it to support more environment standards such as gym and pettingzoo.

• Refactor moss environment.
• Add pettingzoo example.
• Modify file path of agent.
• Fix spec shape of ScaleFeature and OneHotFeature.

Release a new version 0.0.5

Refactor Network to make it more flexible and simpler to custom and compose.

Add vizdoom example(use envpool).

Add Python version img.

Add atari render utils for local test.