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Update README.md

Maxime Chevalier-Boisvert 5 年之前
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      README.md

+ 16 - 16
README.md

@@ -393,6 +393,22 @@ The agent has to pick up a box which is placed in a corner of a 3x3 maze.
 The doors are locked, the keys are hidden in boxes and doors are obstructed
 The doors are locked, the keys are hidden in boxes and doors are obstructed
 by balls. This environment can be solved without relying on language.
 by balls. This environment can be solved without relying on language.
 
 
+## Distributional shift environment
+
+Registered configurations:
+- `MiniGrid-DistShift1-v0`
+- `MiniGrid-DistShift2-v0`
+
+This environment is based on one of the DeepMind [AI safety gridworlds](https://github.com/deepmind/ai-safety-gridworlds).
+The agent starts in the top-left corner and must reach the goal which is in the top-right corner, but has to avoid stepping
+into lava on its way. The aim of this environment is to test an agent's ability to generalize. There are two slightly
+different variants of the environment, so that the agent can be trained on one variant and tested on the other.
+
+<p align="center">
+  <img src="figures/DistShift1.png" width="200">
+  <img src="figures/DistShift2.png" width="200">
+</p>
+
 ## Lava gap environment
 ## Lava gap environment
 
 
 Registered configurations:
 Registered configurations:
@@ -431,22 +447,6 @@ has a single crossing point which can be safely used;  Luckily, a path to the
 goal is guaranteed to exist. This environment is useful for studying safety and
 goal is guaranteed to exist. This environment is useful for studying safety and
 safe exploration.
 safe exploration.
 
 
-## Distributional shift environment
-
-Registered configurations:
-- `MiniGrid-DistShift1-v0`
-- `MiniGrid-DistShift2-v0`
-
-This environment is based on one of the DeepMind [AI safety gridworlds](https://github.com/deepmind/ai-safety-gridworlds).
-The agent starts in the top-left corner and must reach the goal which is in the top-right corner, but has to avoid stepping
-into lava on its way. The aim of this environment is to test an agent's ability to generalize. There are two slightly
-different variants of the environment, so that the agent can be trained on one variant and tested on the other.
-
-<p align="center">
-  <img src="figures/DistShift1.png" width="200">
-  <img src="figures/DistShift2.png" width="200">
-</p>
-
 ## Simple crossing environment
 ## Simple crossing environment
 
 
 Registered configurations:
 Registered configurations: