Merge branch 'gail' of https://github.com/andrewliao11/baselines into gail

baselines/gail/README.md

@@ -8,9 +8,7 @@ For results benchmarking on MuJoCo, please navigate to [here](result/gail-result
 
 ### Step 1: Download expert data
 
-Download the expert data into `./data`
-
-Download [Link](https://drive.google.com/drive/folders/1h-bK09Emrteu7vUXllZLRqTx7iNOaxGI?usp=sharing)
+Download the expert data into `./data`, [download link](https://drive.google.com/drive/folders/1h3H4AY_ZBx08hz-Ct0Nxxus-V1melu1U?usp=sharing)
 
 ### Step 2: Run GAIL
 
@@ -36,6 +34,11 @@ python -m baselines.gail.behavior_clone
 
 See help (`-h`) for more options.
 
-## Reference repositories
+## Others
+
+Thanks to the open source:
+
 - @openai/imitation
 - @carpedm20/deep-rl-tensorflow
+
+Also, thanks [Ryan Jilian](https://github.com/ryanjulian) for reviewing the code

baselines/gail/result/gail-result.md

@@ -1,10 +1,29 @@
-# Results for GAIL on Mujoco
+# Results of GAIL/BC on Mujoco
 
-Here's the extensive results for applying GAIL/BC on Mujoco environments, including 
-Hopper, Walker2d, HalfCheetah, Humanoid, HumanoidStandup. Eery imitator is evaluated with seed to be 0.
+Here's the extensive experimental results of applying GAIL/BC on Mujoco environments, including 
+Hopper-v1, Walker2d-v1, HalfCheetah-v1, Humanoid-v1, HumanoidStandup-v1. Every imitator is evaluated with seed to be 0.
 
 ## Results
 
+### Training through iterations
+
+- Hoppers-v1
+<img src='hopper-training.png'> 
+
+- HalfCheetah-v1
+<img src='halfcheetah-training.png'> 
+
+- Walker2d-v1
+<img src='walker2d-training.png'> 
+
+- Humanoid-v1
+<img src='humanoid-training.png'> 
+
+- HumanoidStandup-v1
+<img src='humanoidstandup-training.png'> 
+
+For details (e.g., adversarial loss, discriminator accuracy, etc.) about GAIL training, please see [here](https://drive.google.com/drive/folders/1nnU8dqAV9i37-_5_vWIspyFUJFQLCsDD?usp=sharing)
+
 ### Determinstic Polciy (Set std=0)
 |   | Un-normalized | Normalized |
 |---|---|---|