update of api docstrings across coach and tutorials [WIP] (#91)

* updating the documentation website
* adding the built docs
* update of api docstrings across coach and tutorials 0-2
* added some missing api documentation
* New Sphinx based documentation

rl_coach/environments/doom_environment.py

@@ -125,6 +125,36 @@ class DoomEnvironment(Environment):
     def __init__(self, level: LevelSelection, seed: int, frame_skip: int, human_control: bool,
                  custom_reward_threshold: Union[int, float], visualization_parameters: VisualizationParameters,
                  cameras: List[CameraTypes], target_success_rate: float=1.0, **kwargs):
+        """
+        :param level: (str)
+            A string representing the doom level to run. This can also be a LevelSelection object.
+            This should be one of the levels defined in the DoomLevel enum. For example, HEALTH_GATHERING.
+
+        :param seed: (int)
+            A seed to use for the random number generator when running the environment.
+
+        :param frame_skip: (int)
+            The number of frames to skip between any two actions given by the agent. The action will be repeated
+            for all the skipped frames.
+
+        :param human_control: (bool)
+            A flag that allows controlling the environment using the keyboard keys.
+
+        :param custom_reward_threshold: (float)
+            Allows defining a custom reward that will be used to decide when the agent succeeded in passing the environment.
+
+        :param visualization_parameters: (VisualizationParameters)
+            The parameters used for visualizing the environment, such as the render flag, storing videos etc.
+
+        :param cameras: (List[CameraTypes])
+            A list of camera types to use as observation in the state returned from the environment.
+            Each camera should be an enum from CameraTypes, and there are several options like an RGB observation,
+            a depth map, a segmentation map, and a top down map of the enviornment.
+
+		:param target_success_rate: (float)
+			Stop experiment if given target success rate was achieved.
+
+        """
         super().__init__(level, seed, frame_skip, human_control, custom_reward_threshold, visualization_parameters, target_success_rate)
 
         self.cameras = cameras