initial

LICENSE.md

@@ -1,6 +1,7 @@
 The MIT License
 
-Copyright (c) 2016 OpenAI (https://openai.com)
+Copyright (c) 2016 OpenAI
+Copyright (c) 2022 Farama Foundation
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal
@@ -19,16 +20,3 @@ AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
 THE SOFTWARE.
-
-# Mujoco models
-This work is derived from [MuJuCo models](http://www.mujoco.org/forum/index.php?resources/) used under the following license:
-```
-This file is part of MuJoCo.     
-Copyright 2009-2015 Roboti LLC.	
-Mujoco		:: Advanced physics simulation engine
-Source		: www.roboti.us
-Version		: 1.31
-Released 	: 23Apr16
-Author		:: Vikash Kumar
-Contacts 	: kumar@roboti.us
-```

gym/core.py

@@ -33,7 +33,7 @@ RenderFrame = TypeVar("RenderFrame")
 
 
 class Env(Generic[ObsType, ActType]):
-    r"""The main OpenAI Gym class.
+    r"""The main Gym class.
 
     It encapsulates an environment with arbitrary behind-the-scenes dynamics.
     An environment can be partially or fully observed.

gym/envs/classic_control/acrobot.py

@@ -110,8 +110,7 @@ class AcrobotEnv(core.Env):
     env.env.book_or_nips = 'nips'
     ```
 
-    See the following note and
-    the [implementation](https://github.com/openai/gym/blob/master/gym/envs/classic_control/acrobot.py) for details:
+    See the following note for details:
 
     > The dynamics equations were missing some terms in the NIPS paper which
             are present in the book. R. Sutton confirmed in personal correspondence

gym/envs/classic_control/pendulum.py

@@ -109,8 +109,8 @@ class PendulumEnv(gym.Env):
 
         high = np.array([1.0, 1.0, self.max_speed], dtype=np.float32)
         # This will throw a warning in tests/envs/test_envs in utils/env_checker.py as the space is not symmetric
-        #   or normalised as max_torque == 2 by default. Ignoring the issue here as the default settings are too old
-        #   to update to follow the openai gym api
+        #   or normalized as max_torque == 2 by default. Ignoring the issue here as the default settings are too old
+        #   to update to follow the Gym api
         self.action_space = spaces.Box(
             low=-self.max_torque, high=self.max_torque, shape=(1,), dtype=np.float32
         )

gym/wrappers/normalize.py

@@ -3,8 +3,6 @@ import numpy as np
 
 import gym
 
-
-# taken from https://github.com/openai/baselines/blob/master/baselines/common/vec_env/vec_normalize.py
 class RunningMeanStd:
     """Tracks the mean, variance and count of values."""