Merge pull request #1005 from Unity-Technologies/hotfix-0.4b

Hotfix 0.4b

docs/Learning-Environment-Examples.md

     * -0.0025 for every step.
     * +1.0 if the block touches the goal.
 * Brains: One brain with the following observation/action space.
-    * Vector Observation space: 15 variables corresponding to position and velocities of agent, block, and goal.
+    * Vector Observation space: (Continuous) 70 variables corresponding to 14 ray-casts each detecting one of three possible objects (wall, goal, or block).
     * Vector Action space: (Continuous) Size of 2, corresponding to movement in X and Z directions.
     * Visual Observations (Optional): One first-person camera. Use `VisualPushBlock` scene.
 * Reset Parameters: None.

python/unityagents/rpc_communicator.py

 
 
 class UnityToExternalServicerImplementation(UnityToExternalServicer):
-    parent_conn, child_conn = Pipe()
+    def __init__(self):
+        self.parent_conn, self.child_conn = Pipe()
 
     def Initialize(self, request, context):
         self.child_conn.send(request)

unity-environment/Assets/ML-Agents/Scripts/Agent.cs

         void OnEnable()
         {
             textureArray = new Texture2D[agentParameters.agentCameras.Count];
-            for (int i = 0; i < brain.brainParameters.cameraResolutions.Length; i++)
+            for (int i = 0; i < agentParameters.agentCameras.Count; i++)
-                textureArray[i] = new Texture2D(brain.brainParameters.cameraResolutions[i].width, 
-                    brain.brainParameters.cameraResolutions[i].height, TextureFormat.RGB24, false);
+                textureArray[i] = new Texture2D(1, 1, TextureFormat.RGB24, false);
             }
             id = gameObject.GetInstanceID();
             Academy academy = Object.FindObjectOfType<Academy>() as Academy;