Merge pull request #384 from Unity-Technologies/hotfix/issue#333

hotfix on issue#333, and a few comments fixes

unity-environment/Assets/ML-Agents/Editor/AgentEditor.cs

         EditorGUILayout.PropertyField(brain);
 
         EditorGUILayout.LabelField("Agent Cameras");
-		for (int i = 0; i < cameras.arraySize; i++)
-		{
-			EditorGUILayout.PropertyField(cameras.GetArrayElementAtIndex(i), new GUIContent("Camera " + (i + 1).ToString() + ": "));
-		}
+        for (int i = 0; i < cameras.arraySize; i++)
+        {
+            EditorGUILayout.PropertyField(cameras.GetArrayElementAtIndex(i), new GUIContent("Camera " + (i + 1).ToString() + ": "));
+        }
-		if (GUILayout.Button("Remove Camera", EditorStyles.miniButton))
-		{
-			cameras.arraySize--;
-		}
+        if (GUILayout.Button("Remove Camera", EditorStyles.miniButton))
+        {
+            cameras.arraySize--;
+        }
-		
+        
-                                		"The per-agent maximum number of steps."));
+                                        "The per-agent maximum number of steps."));
         EditorGUILayout.PropertyField(isResetOnDone, new GUIContent("Reset On Done",
                          "If checked, the agent will reset on done. Else, AgentOnDone() will be called."));
         EditorGUILayout.PropertyField(isEBS, new GUIContent("On Demand Decision", "If checked, you must manually request decisions."));
             actionsPerDecision.intValue = Mathf.Max(1, actionsPerDecision.intValue);
         }
 
-		serializedAgent.ApplyModifiedProperties();
+        serializedAgent.ApplyModifiedProperties();
 
         EditorGUILayout.LabelField("", GUI.skin.horizontalSlider);
         base.OnInspectorGUI();

unity-environment/Assets/ML-Agents/Editor/BrainEditor.cs

     [SerializeField]
     bool _Foldout = true;
 
-	public override void OnInspectorGUI ()
-	{
-		Brain myBrain = (Brain)target;
-		SerializedObject serializedBrain = serializedObject;
+    public override void OnInspectorGUI ()
+    {
+        Brain myBrain = (Brain)target;
+        SerializedObject serializedBrain = serializedObject;
-		if (myBrain.transform.parent == null) {
-			EditorGUILayout.HelpBox ("A Brain GameObject must be a child of an Academy GameObject!", MessageType.Error);
-		} else if (myBrain.transform.parent.GetComponent<Academy> () == null) {
-			EditorGUILayout.HelpBox ("The Parent of a Brain must have an Academy Component attached to it!", MessageType.Error);
-		}
+        if (myBrain.transform.parent == null) {
+            EditorGUILayout.HelpBox ("A Brain GameObject must be a child of an Academy GameObject!", MessageType.Error);
+        } else if (myBrain.transform.parent.GetComponent<Academy> () == null) {
+            EditorGUILayout.HelpBox ("The Parent of a Brain must have an Academy Component attached to it!", MessageType.Error);
+        }
-		BrainParameters parameters = myBrain.brainParameters;
+        BrainParameters parameters = myBrain.brainParameters;
-		
-		serializedBrain.Update();
-		
+        
+        serializedBrain.Update();
+        
 
         _Foldout = EditorGUILayout.Foldout(_Foldout, "Brain Parameters");
         int indentLevel = EditorGUI.indentLevel;
 
         }
         EditorGUI.indentLevel = indentLevel;
-		SerializedProperty bt = serializedBrain.FindProperty("brainType");
-		EditorGUILayout.PropertyField(bt);
+        SerializedProperty bt = serializedBrain.FindProperty("brainType");
+        EditorGUILayout.PropertyField(bt);
-		if (bt.enumValueIndex < 0) {
-			bt.enumValueIndex = (int)BrainType.Player;
-		}
+        if (bt.enumValueIndex < 0) {
+            bt.enumValueIndex = (int)BrainType.Player;
+        }
-		serializedBrain.ApplyModifiedProperties();
+        serializedBrain.ApplyModifiedProperties();
-		myBrain.UpdateCoreBrains ();
-		myBrain.coreBrain.OnInspector ();
+        myBrain.UpdateCoreBrains ();
+        myBrain.coreBrain.OnInspector ();
-		#if !NET_4_6 && ENABLE_TENSORFLOW
-		EditorGUILayout.HelpBox ("You cannot have ENABLE_TENSORFLOW without NET_4_6", MessageType.Error);
-		#endif
-	}
+        #if !NET_4_6 && ENABLE_TENSORFLOW
+        EditorGUILayout.HelpBox ("You cannot have ENABLE_TENSORFLOW without NET_4_6", MessageType.Error);
+        #endif
+    }
 }

unity-environment/Assets/ML-Agents/Editor/MLAgentsEditModeTest.cs

             Assert.AreEqual(0, aca.stepsSinceReset);
             Assert.AreEqual(0, aca.episodeCount);
             Assert.AreEqual(false, aca.IsDone());
-            //This will call the method even though it is private
+            // This will call the method even though it is private
             MethodInfo AcademyInitializeMethod = typeof(Academy).GetMethod("_InitializeAcademy",
                            BindingFlags.Instance | BindingFlags.NonPublic);
             AcademyInitializeMethod.Invoke(aca, new object[] { });

unity-environment/Assets/ML-Agents/Examples/3DBall/Scripts/Ball3DDecision.cs

 
 public class Ball3DDecision : MonoBehaviour, Decision
 {
+    public float rotationSpeed = 2f;
+
-            List<float> ret = new List<float>();
-            if (state[2] < 0 || state[5] < 0)
-            {
-                ret.Add(state[5]);
-            }
-            else
-            {
-                ret.Add(state[5]);
-            }
-            if (state[3] < 0 || state[7] < 0)
-            {
-                ret.Add(-state[7]);
-            }
-            else
-            {
-                ret.Add(-state[7]);
-            }
-            return ret.ToArray();
+            List<float> act = new List<float>();
+
+            // state[5] is the velocity of the ball in the x orientation. 
+            // We use this number to control the Platform's z axis rotation speed, 
+            // so that the Platform is tilted in the x orientation correspondingly. 
+            act.Add(state[5] * rotationSpeed);
+
+            // state[7] is the velocity of the ball in the z orientation. 
+            // We use this number to control the Platform's x axis rotation speed,  
+            // so that the Platform is tilted in the z orientation correspondingly. 
+            act.Add(-state[7] * rotationSpeed);
+            return act.ToArray();
+
+        // If the vector action space type is discrete, then we don't do anything.     
         else
         {
             return new float[1]{ 1f };

unity-environment/Assets/ML-Agents/Examples/Area/Scripts/Area.cs

 
 public class Area : MonoBehaviour {
 
-	// Use this for initialization
-	void Start () {
-		
-	}
-	
-	// Update is called once per frame
-	void Update () {
-		
-	}
+    // Use this for initialization
+    void Start () {
+        
+    }
+    
+    // Update is called once per frame
+    void Update () {
+        
+    }
 
     public virtual void ResetArea() {
         

unity-environment/Assets/ML-Agents/Examples/Area/Scripts/AreaAgent.cs

     public override void CollectObservations()
     {
         Vector3 velocity = GetComponent<Rigidbody>().velocity;
-		AddVectorObs((transform.position.x - area.transform.position.x));
-		AddVectorObs((transform.position.y - area.transform.position.y));
-		AddVectorObs((transform.position.z + 5 - area.transform.position.z));
-		AddVectorObs(velocity.x);
-		AddVectorObs(velocity.y);
-		AddVectorObs(velocity.z);
-	}
+        AddVectorObs((transform.position.x - area.transform.position.x));
+        AddVectorObs((transform.position.y - area.transform.position.y));
+        AddVectorObs((transform.position.z + 5 - area.transform.position.z));
+        AddVectorObs(velocity.x);
+        AddVectorObs(velocity.y);
+        AddVectorObs(velocity.z);
+    }
 
     public void MoveAgent(float[] act) {
         float directionX = 0;
         AddReward(-0.005f);
         MoveAgent(vectorAction);
 
-		if (gameObject.transform.position.y < 0.0f || Mathf.Abs(gameObject.transform.position.x - area.transform.position.x) > 8f || 
+        if (gameObject.transform.position.y < 0.0f || Mathf.Abs(gameObject.transform.position.x - area.transform.position.x) > 8f || 
-		{
+        {
-		}
-	}
+        }
+    }
-	public override void AgentReset()
-	{
-		transform.position = new Vector3(Random.Range(-3.5f, 3.5f), 1.1f, -8f) + area.transform.position;
-		GetComponent<Rigidbody>().velocity = new Vector3(0f, 0f, 0f);
+    public override void AgentReset()
+    {
+        transform.position = new Vector3(Random.Range(-3.5f, 3.5f), 1.1f, -8f) + area.transform.position;
+        GetComponent<Rigidbody>().velocity = new Vector3(0f, 0f, 0f);
-		area.GetComponent<Area>().ResetArea();
-	}
+        area.GetComponent<Area>().ResetArea();
+    }
 
 }

unity-environment/Assets/ML-Agents/Examples/Area/Scripts/AreaDecision.cs

 public class AreaDecision : MonoBehaviour, Decision {
 
     public float[] Decide (List<float> state, List<Texture2D> observation, float reward, bool done, List<float> memory)
-	{
+    {
-	}
+    }
-	public List<float> MakeMemory (List<float> state, List<Texture2D> observation, float reward, bool done, List<float> memory)
-	{
-		return new List<float>();
-		
-	}
+    public List<float> MakeMemory (List<float> state, List<Texture2D> observation, float reward, bool done, List<float> memory)
+    {
+        return new List<float>();
+        
+    }
 }

unity-environment/Assets/ML-Agents/Examples/Area/Scripts/GoalInteract.cs

             agent.Done();
             agent.AddReward(1f);
         }
-	}
+    }
 
 }

unity-environment/Assets/ML-Agents/Examples/Area/Scripts/Push/PushAcademy.cs

     public float blockSize;
     public float xVariation;
 
-	public override void AcademyReset()
-	{
+    public override void AcademyReset()
+    {
-	}
+    }
-	public override void AcademyStep()
-	{
+    public override void AcademyStep()
+    {
-	}
+    }
 
 }

unity-environment/Assets/ML-Agents/Examples/Area/Scripts/Push/PushAgent.cs

 
 public class PushAgent : AreaAgent
 {
-	public GameObject goalHolder;
+    public GameObject goalHolder;
     public GameObject block;
 
     Rigidbody rb;
 
     public override void InitializeAgent()
     {
-		base.InitializeAgent();
+        base.InitializeAgent();
-	public override void CollectObservations()
-	{
+    public override void CollectObservations()
+    {
         velocity = rb.velocity;
         blockVelocity = block.GetComponent<Rigidbody>().velocity;
         AddVectorObs((transform.position.x - area.transform.position.x));
         AddVectorObs((block.transform.position.y - area.transform.position.y));
         AddVectorObs((block.transform.position.z + 5 - area.transform.position.z));
 
-		AddVectorObs(velocity.x);
-		AddVectorObs(velocity.y);
-		AddVectorObs(velocity.z);
+        AddVectorObs(velocity.x);
+        AddVectorObs(velocity.y);
+        AddVectorObs(velocity.z);
-		AddVectorObs(blockVelocity.x);
-		AddVectorObs(blockVelocity.y);
-		AddVectorObs(blockVelocity.z);
+        AddVectorObs(blockVelocity.x);
+        AddVectorObs(blockVelocity.y);
+        AddVectorObs(blockVelocity.z);
-	}
+    }
 
     public override void AgentAction(float[] vectorAction, string textAction)
 	{
         if (gameObject.transform.position.y < 0.0f || Mathf.Abs(gameObject.transform.position.x - area.transform.position.x) > 8f ||
             Mathf.Abs(gameObject.transform.position.z + 5 - area.transform.position.z) > 8)
-		{
+        {
-		}
-	}
+        }
+    }
-	public override void AgentReset()
-	{
+    public override void AgentReset()
+    {
-		rb.velocity = new Vector3(0f, 0f, 0f);
+        rb.velocity = new Vector3(0f, 0f, 0f);
-	}
+    }
-	public override void AgentOnDone()
-	{
+    public override void AgentOnDone()
+    {
-	}
+    }
 }

unity-environment/Assets/ML-Agents/Examples/Area/Scripts/Push/PushArea.cs

     public GameObject goalHolder;
     public GameObject academy;
 
-	// Use this for initialization
-	void Start () {
-		academy = GameObject.Find("Academy");
-	}
-	
-	// Update is called once per frame
-	void Update () {
-		
-	}
+    // Use this for initialization
+    void Start () {
+        academy = GameObject.Find("Academy");
+    }
+    
+    // Update is called once per frame
+    void Update () {
+        
+    }
-	public override void ResetArea()
-	{
+    public override void ResetArea()
+    {
         float goalSize = academy.GetComponent<PushAcademy>().goalSize;
         float blockSize = academy.GetComponent<PushAcademy>().blockSize;
         float xVariation = academy.GetComponent<PushAcademy>().xVariation;
         blockSize = Random.Range(blockSize * 0.9f, blockSize * 1.1f);
         block.transform.localScale = new Vector3(blockSize, 1f, blockSize);
         goalHolder.transform.localScale = new Vector3(goalSize, 1f, goalSize);
-	}
+    }
 
 }

unity-environment/Assets/ML-Agents/Examples/Area/Scripts/Wall/WallAcademy.cs

     public float minWallHeight;
     public float maxWallHeight;
 
-	public override void AcademyReset()
-	{
+    public override void AcademyReset()
+    {
-	}
+    }
-	public override void AcademyStep()
-	{
+    public override void AcademyStep()
+    {
 
     }
 

unity-environment/Assets/ML-Agents/Examples/Area/Scripts/Wall/WallAgent.cs

 
 public class WallAgent : AreaAgent
 {
-	public GameObject goalHolder;
+    public GameObject goalHolder;
-		base.InitializeAgent();
+        base.InitializeAgent();
-	public override void CollectObservations()
-	{
+    public override void CollectObservations()
+    {
         Vector3 velocity = GetComponent<Rigidbody>().velocity;
         AddVectorObs((transform.position.x - area.transform.position.x));
         AddVectorObs((transform.position.y - area.transform.position.y));
         AddVectorObs((block.transform.position.y - area.transform.position.y));
         AddVectorObs((block.transform.position.z + 5 - area.transform.position.z));
 
-		AddVectorObs(wall.transform.localScale.y);
+        AddVectorObs(wall.transform.localScale.y);
-		AddVectorObs(velocity.x);
-		AddVectorObs(velocity.y);
-		AddVectorObs(velocity.z);
+        AddVectorObs(velocity.x);
+        AddVectorObs(velocity.y);
+        AddVectorObs(velocity.z);
-		AddVectorObs(blockVelocity.x);
-		AddVectorObs(blockVelocity.y);
-		AddVectorObs(blockVelocity.z);
-	}
+        AddVectorObs(blockVelocity.x);
+        AddVectorObs(blockVelocity.y);
+        AddVectorObs(blockVelocity.z);
+    }
 
     public override void AgentAction(float[] vectorAction, string textAction)
 	{
         if (gameObject.transform.position.y < 0.0f ||
             Mathf.Abs(gameObject.transform.position.x - area.transform.position.x) > 8f ||
             Mathf.Abs(gameObject.transform.position.z + 5 - area.transform.position.z) > 8)
-		{
+        {
-		}
-	}
+        }
+    }
-	public override void AgentReset()
-	{
-		transform.position = new Vector3(Random.Range(-3.5f, 3.5f), 1.1f, -8f) + area.transform.position;
-		GetComponent<Rigidbody>().velocity = new Vector3(0f, 0f, 0f);
+    public override void AgentReset()
+    {
+        transform.position = new Vector3(Random.Range(-3.5f, 3.5f), 1.1f, -8f) + area.transform.position;
+        GetComponent<Rigidbody>().velocity = new Vector3(0f, 0f, 0f);
-	}
+    }
-	public override void AgentOnDone()
-	{
+    public override void AgentOnDone()
+    {
-	}
+    }
 }

unity-environment/Assets/ML-Agents/Examples/Area/Scripts/Wall/WallArea.cs

     public GameObject block;
     public GameObject goalHolder;
 
-	// Use this for initialization
-	void Start () {
-		academy = GameObject.Find("Academy");
-	}
-	
-	// Update is called once per frame
-	void Update () {
-		
-	}
+    // Use this for initialization
+    void Start () {
+        academy = GameObject.Find("Academy");
+    }
+    
+    // Update is called once per frame
+    void Update () {
+        
+    }
-		wall.transform.localScale = new Vector3(12f, Random.Range(wallHeightMin, wallHeightMax) - 0.1f, 1f);
+        wall.transform.localScale = new Vector3(12f, Random.Range(wallHeightMin, wallHeightMax) - 0.1f, 1f);
-		goalHolder.transform.position = new Vector3(Random.Range(-3.5f, 3.5f), -0.1f, 0f) + gameObject.transform.position;
-	}
+        goalHolder.transform.position = new Vector3(Random.Range(-3.5f, 3.5f), -0.1f, 0f) + gameObject.transform.position;
+    }
 }

unity-environment/Assets/ML-Agents/Examples/Banana/Scripts/BananaAgent.cs

     public override void InitializeAgent()
     {
         base.InitializeAgent();
-        agentRB = GetComponent<Rigidbody>(); //cache the RB
+        agentRB = GetComponent<Rigidbody>(); // cache the RB
         Monitor.verticalOffset = 1f;
         myArea = area.GetComponent<BananaArea>();
         myAcademy = myAcademyObj.GetComponent<BananaAcademy>();
             transform.Rotate(rotateDir, Time.deltaTime * turnSpeed);
         }
 
-        if (agentRB.velocity.sqrMagnitude > 25f) //slow it down
+        if (agentRB.velocity.sqrMagnitude > 25f) // slow it down
         {
             agentRB.velocity *= 0.95f;
         }

unity-environment/Assets/ML-Agents/Examples/Banana/Scripts/BananaLogic.cs

     public bool respawn;
     public BananaArea myArea;
 
-	// Use this for initialization
-	void Start () {
-		
-	}
-	
-	// Update is called once per frame
-	void Update () {
-		
-	}
+    // Use this for initialization
+    void Start () {
+        
+    }
+    
+    // Update is called once per frame
+    void Update () {
+        
+    }
 
     public void OnEaten() {
         if (respawn) 

unity-environment/Assets/ML-Agents/Examples/Basic/Scripts/BasicAcademy.cs

 
 public class BasicAcademy : Academy {
 
-	public override void AcademyReset()
-	{
+    public override void AcademyReset()
+    {
-	}
+    }
-	public override void AcademyStep()
-	{
+    public override void AcademyStep()
+    {
-	}
+    }
 
 }

unity-environment/Assets/ML-Agents/Examples/Basic/Scripts/BasicAgent.cs

     private BasicAcademy academy;
     public float timeBetweenDecisionsAtInference;
     private float timeSinceDecision;
-	public int position;
-	public int smallGoalPosition;
-	public int largeGoalPosition;
-	public GameObject largeGoal;
-	public GameObject smallGoal;
-	public int minPosition;
-	public int maxPosition;
+    public int position;
+    public int smallGoalPosition;
+    public int largeGoalPosition;
+    public GameObject largeGoal;
+    public GameObject smallGoal;
+    public int minPosition;
+    public int maxPosition;
 
     public override void InitializeAgent()
     {
-	public override void CollectObservations()
-	{
-		AddVectorObs(position);
-	}
+    public override void CollectObservations()
+    {
+        AddVectorObs(position);
+    }
 
     public override void AgentAction(float[] vectorAction, string textAction)
 	{
 		if (movement == 1) { direction = 1; }
 
-		position += direction;
-		if (position < minPosition) { position = minPosition; }
-		if (position > maxPosition) { position = maxPosition; }
+        position += direction;
+        if (position < minPosition) { position = minPosition; }
+        if (position > maxPosition) { position = maxPosition; }
-		gameObject.transform.position = new Vector3(position, 0f, 0f);
+        gameObject.transform.position = new Vector3(position, 0f, 0f);
-		if (position == smallGoalPosition)
-		{
+        if (position == smallGoalPosition)
+        {
-		}
+        }
-		if (position == largeGoalPosition)
-		{
+        if (position == largeGoalPosition)
+        {
-		}
-	}
+        }
+    }
-	public override void AgentReset()
-	{
-		position = 0;
-		minPosition = -10;
-		maxPosition = 10;
-		smallGoalPosition = -3;
-		largeGoalPosition = 7;
-		smallGoal.transform.position = new Vector3(smallGoalPosition, 0f, 0f);
-		largeGoal.transform.position = new Vector3(largeGoalPosition, 0f, 0f);
-	}
+    public override void AgentReset()
+    {
+        position = 0;
+        minPosition = -10;
+        maxPosition = 10;
+        smallGoalPosition = -3;
+        largeGoalPosition = 7;
+        smallGoal.transform.position = new Vector3(smallGoalPosition, 0f, 0f);
+        largeGoal.transform.position = new Vector3(largeGoalPosition, 0f, 0f);
+    }
-	public override void AgentOnDone()
-	{
+    public override void AgentOnDone()
+    {
-	}
+    }
 
     public void FixedUpdate()
     {

unity-environment/Assets/ML-Agents/Examples/Bouncer/Scripts/BouncerAcademy.cs

 
 public class BouncerAcademy : Academy {
 
-	public override void AcademyReset()
-	{
+    public override void AcademyReset()
+    {
-	}
+    }
-	public override void AcademyStep()
-	{
+    public override void AcademyStep()
+    {
-	}
+    }
 
 }

unity-environment/Assets/ML-Agents/Examples/Bouncer/Scripts/BouncerAgent.cs

         rb.velocity = rb.velocity.normalized * speed;
     }
 
-	public override void CollectObservations()
-	{
+    public override void CollectObservations()
+    {
-	}
+    }
 
     public override void AgentAction(float[] vectorAction, string textAction)
 	{
         }
         else
         {
-            //AddReward(0.05f);
+            // AddReward(0.05f);
-	}
+    }
-	public override void AgentReset()
-	{
+    public override void AgentReset()
+    {
-	}
+    }
-	public override void AgentOnDone()
-	{
+    public override void AgentOnDone()
+    {
-	}
+    }
 
     private void OnTriggerEnter(Collider collision)
     {

unity-environment/Assets/ML-Agents/Examples/Bouncer/Scripts/BouncerBanana.cs

     void Start(){
 
     }
-	
-	// Update is called once per frame
-	void FixedUpdate () {
+    
+    // Update is called once per frame
+    void FixedUpdate () {
-	}
+    }
 
     private void OnTriggerEnter(Collider collision)
     {

unity-environment/Assets/ML-Agents/Examples/Crawler/Scripts/CameraFollow.cs

 
 public class CameraFollow : MonoBehaviour {
 
-	public Transform target;
-	Vector3 offset;
+    public Transform target;
+    Vector3 offset;
-	// Use this for initialization
-	void Start () {
-		offset = gameObject.transform.position - target.position;
-	}
-	
-	// Update is called once per frame
-	void Update () {
-        //gameObject.transform.position = target.position + offset;
+    // Use this for initialization
+    void Start () {
+        offset = gameObject.transform.position - target.position;
+    }
+    
+    // Update is called once per frame
+    void Update () {
+        // gameObject.transform.position = target.position + offset;
-	}
+    }
 }

unity-environment/Assets/ML-Agents/Examples/Hallway/Scripts/HallwayAcademy.cs

 
 public class HallwayAcademy : Academy {
 
-	public float agentRunSpeed; 
-	public float agentRotationSpeed;
-    public Material goalScoredMaterial; //when a goal is scored the ground will use this material for a few seconds.
-    public Material failMaterial; //when fail, the ground will use this material for a few seconds. 
-	public float gravityMultiplier; //use ~3 to make things less floaty
+    public float agentRunSpeed; 
+    public float agentRotationSpeed;
+    public Material goalScoredMaterial; // when a goal is scored the ground will use this material for a few seconds.
+    public Material failMaterial; // when fail, the ground will use this material for a few seconds. 
+    public float gravityMultiplier; // use ~3 to make things less floaty
 
     public override void InitializeAcademy()
     {
-	public override void AcademyReset()
-	{
+    public override void AcademyReset()
+    {
 
     }
 }

unity-environment/Assets/ML-Agents/Examples/Hallway/Scripts/HallwayAgent.cs

-//Put this script on your blue cube.
+// Put this script on your blue cube.
 
 using System.Collections;
 using System.Collections.Generic;
 {
-    public GameObject ground; //ground game object. we will use the area bounds to spawn the blocks
+    public GameObject ground; // ground game object. we will use the area bounds to spawn the blocks
-    public GameObject orangeBlock; //the orange block we are going to be pushing
+    public GameObject orangeBlock; // the orange block we are going to be pushing
-    Rigidbody shortBlockRB;  //cached on initialization
-    Rigidbody agentRB;  //cached on initialization
-    Material groundMaterial; //cached on Awake()
+    Rigidbody shortBlockRB;  // cached on initialization
+    Rigidbody agentRB;  // cached on initialization
+    Material groundMaterial; // cached on Awake()
     Renderer groundRenderer;
     HallwayAcademy academy;
 
     {
         base.InitializeAgent();
         academy = FindObjectOfType<HallwayAcademy>();
-        brain = FindObjectOfType<Brain>(); //only one brain in the scene so this should find our brain. BRAAAINS.
+        brain = FindObjectOfType<Brain>(); // only one brain in the scene so this should find our brain. BRAAAINS.
-        agentRB = GetComponent<Rigidbody>(); //cache the agent rigidbody
-        groundRenderer = ground.GetComponent<Renderer>(); //get the ground renderer so we can change the material when a goal is scored
-        groundMaterial = groundRenderer.material; //starting material
+        agentRB = GetComponent<Rigidbody>(); // cache the agent rigidbody
+        groundRenderer = ground.GetComponent<Renderer>(); // get the ground renderer so we can change the material when a goal is scored
+        groundMaterial = groundRenderer.material; // starting material
 
     }
 
         RayPerception(rayDistance, rayAngles, detectableObjects, 0f);
     }
 
-    //swap ground material, wait time seconds, then swap back to the regular ground material.
+    // swap ground material, wait time seconds, then swap back to the regular ground material.
-        yield return new WaitForSeconds(time); //wait for 2 sec
+        yield return new WaitForSeconds(time); // wait for 2 sec
         groundRenderer.material = groundMaterial;
     }
 
         Vector3 dirToGo = Vector3.zero;
         Vector3 rotateDir = Vector3.zero;
 
-        //If we're using Continuous control you will need to change the Action
+
+        // If we're using Continuous control you will need to change the Action
         if (brain.brainParameters.vectorActionSpaceType == SpaceType.continuous)
         {
             dirToGo = transform.forward * Mathf.Clamp(act[0], -1f, 1f);
             }
         }
         transform.Rotate(rotateDir, Time.deltaTime * 100f);
-        agentRB.AddForce(dirToGo * academy.agentRunSpeed, ForceMode.VelocityChange); //GO
+        agentRB.AddForce(dirToGo * academy.agentRunSpeed, ForceMode.VelocityChange); // GO
     }
 
     public override void AgentAction(float[] vectorAction, string textAction)
         MoveAgent(vectorAction); //perform agent actions
         bool fail = false;  // did the agent or block get pushed off the edge?
 
-        if (!Physics.Raycast(agentRB.position, Vector3.down, 20)) //if the agent has gone over the edge, we done.
+        if (!Physics.Raycast(agentRB.position, Vector3.down, 20)) // if the agent has gone over the edge, we done.
-            fail = true; //fell off bro
+            fail = true; // fell off bro
-            Done(); //if we mark an agent as done it will be reset automatically. AgentReset() will be called.
+            Done(); // if we mark an agent as done it will be reset automatically. AgentReset() will be called.
-            StartCoroutine(GoalScoredSwapGroundMaterial(academy.failMaterial, .5f)); //swap ground material to indicate fail
+            StartCoroutine(GoalScoredSwapGroundMaterial(academy.failMaterial, .5f)); // swap ground material to indicate fail
         }
     }
 
-        if (col.gameObject.CompareTag("goal")) //touched goal
+        if (col.gameObject.CompareTag("goal")) // touched goal
-                AddReward(1f); //you get 5 points
-                StartCoroutine(GoalScoredSwapGroundMaterial(academy.goalScoredMaterial, 2)); //swap ground material for a bit to indicate we scored.
+                AddReward(1f); // you get 5 points
+                StartCoroutine(GoalScoredSwapGroundMaterial(academy.goalScoredMaterial, 2)); // swap ground material for a bit to indicate we scored.
-                AddReward(-0.1f); //you lose a point
-                StartCoroutine(GoalScoredSwapGroundMaterial(academy.failMaterial, .5f)); //swap ground material to indicate fail
+                AddReward(-0.1f); // you lose a point
+                StartCoroutine(GoalScoredSwapGroundMaterial(academy.failMaterial, .5f)); // swap ground material to indicate fail
-            Done(); //if we mark an agent as done it will be reset automatically. AgentReset() will be called.
+            Done(); // if we mark an agent as done it will be reset automatically. AgentReset() will be called.
-    //In the editor, if "Reset On Done" is checked then AgentReset() will be called automatically anytime we mark done = true in an agent script.
+    // In the editor, if "Reset On Done" is checked then AgentReset() will be called automatically anytime we mark done = true in an agent script.
     public override void AgentReset()
     {
         selection = Random.Range(0, 2);

unity-environment/Assets/ML-Agents/Examples/Reacher/Scripts/FlyCamera.cs

     space : Moves camera on X and Z axis only.  So camera doesn't gain any height*/
 
 
-    public float mainSpeed = 100.0f; //regular speed
-    public float shiftAdd = 250.0f; //multiplied by how long shift is held.  Basically running
-    public float maxShift = 1000.0f; //Maximum speed when holdin gshift
-    public float camSens = 0.25f; //How sensitive it with mouse
+    public float mainSpeed = 100.0f; // regular speed
+    public float shiftAdd = 250.0f; // multiplied by how long shift is held.  Basically running
+    public float maxShift = 1000.0f; // Maximum speed when holdin gshift
+    public float camSens = 0.25f; // How sensitive it with mouse
-    private Vector3 lastMouse = new Vector3(255, 255, 255); //kind of in the middle of the screen, rather than at the top (play)
+    private Vector3 lastMouse = new Vector3(255, 255, 255); // kind of in the middle of the screen, rather than at the top (play)
     private float totalRun = 1.0f;
 
     void Awake()
-                                                                    //transform.position.Set(0,8,-32);
-                                                                    //transform.rotation.Set(15,0,0,1);
+                                                                    // transform.position.Set(0,8,-32);
+                                                                    // transform.rotation.Set(15,0,0,1);
         transform.position = new Vector3(0, 8, -32);
         transform.rotation = Quaternion.Euler(25, 0, 0);
     }
             lastMouse = new Vector3(transform.eulerAngles.x + lastMouse.x, transform.eulerAngles.y + lastMouse.y, 0);
             transform.eulerAngles = lastMouse;
             lastMouse = Input.mousePosition;
-            //Mouse  camera angle done.  
+            // Mouse  camera angle done.  
-        //Keyboard commands
+        // Keyboard commands
         Vector3 p = GetBaseInput();
         if (Input.GetKey(KeyCode.LeftShift))
         {
         Vector3 newPosition = transform.position;
         if (Input.GetKey(KeyCode.Space)
             || (movementStaysFlat && !(rotateOnlyIfMousedown && Input.GetMouseButton(1))))
-        { //If player wants to move on X and Z axis only
+        { // If player wants to move on X and Z axis only
             transform.Translate(p);
             newPosition.x = transform.position.x;
             newPosition.z = transform.position.z;
     }
 
     private Vector3 GetBaseInput()
-    { //returns the basic values, if it's 0 than it's not active.
+    { // returns the basic values, if it's 0 than it's not active.
         Vector3 p_Velocity = new Vector3();
         if (Input.GetKey(KeyCode.W))
         {

unity-environment/Assets/ML-Agents/Examples/Reacher/Scripts/ReacherAcademy.cs

     public float goalSpeed;
 
 
-	public override void AcademyReset()
-	{
+    public override void AcademyReset()
+    {
-	}
+    }
-	public override void AcademyStep()
-	{
+    public override void AcademyStep()
+    {
-	}
+    }
 
 }

unity-environment/Assets/ML-Agents/Examples/Reacher/Scripts/ReacherAgent.cs

     /// We collect the normalized rotations, angularal velocities, and velocities of both
     /// limbs of the reacher as well as the relative position of the target and hand.
     /// </summary>
-	public override void CollectObservations()
-	{
+    public override void CollectObservations()
+    {
         AddVectorObs(pendulumA.transform.rotation.eulerAngles.x / 180.0f - 1.0f);
         AddVectorObs(pendulumA.transform.rotation.eulerAngles.y / 180.0f - 1.0f);
         AddVectorObs(pendulumA.transform.rotation.eulerAngles.z / 180.0f - 1.0f);
 
         goal.transform.localScale = new Vector3(goalSize, goalSize, goalSize);
     }
-
 }

unity-environment/Assets/ML-Agents/Examples/Reacher/Scripts/ReacherDecision.cs

 public class ReacherDecision : MonoBehaviour, Decision {
 
     public float[] Decide (List<float> state, List<Texture2D> observation, float reward, bool done, List<float> memory)
-	{
+    {
         float[] action = new float[4];
         for (int i = 0; i < 4; i++) {
             action[i] = Random.Range(-1f, 1f);
-	}
+    }
-	{
-		return new List<float>();
-		
-	}
+    {
+        return new List<float>();
+        
+    }
 }

unity-environment/Assets/ML-Agents/Examples/Reacher/Scripts/ReacherGoal.cs

     public GameObject hand;
     public GameObject goalOn;
 
-	// Use this for initialization
-	void Start () {
-		
-	}
-	
-	// Update is called once per frame
-	void Update () {
-		
-	}
+    // Use this for initialization
+    void Start () {
+        
+    }
+    
+    // Update is called once per frame
+    void Update () {
+        
+    }
 
     private void OnTriggerEnter(Collider other)
     {

unity-environment/Assets/ML-Agents/Examples/Tennis/Scripts/TennisArea.cs

     public GameObject agentA;
     public GameObject agentB;
 
-	// Use this for initialization
-	void Start () {
+    // Use this for initialization
+    void Start () {
-	}
-	
-	// Update is called once per frame
-	void Update () {
-		
-	}
+    }
+    
+    // Update is called once per frame
+    void Update () {
+        
+    }
 
     public void MatchReset() {
         float ballOut = Random.Range(6f, 8f);

unity-environment/Assets/ML-Agents/Examples/Tennis/Scripts/hitWall.cs

 
 public class hitWall : MonoBehaviour
 {
-	public GameObject areaObject;
-	public int lastAgentHit;
+    public GameObject areaObject;
+    public int lastAgentHit;
-	// Use this for initialization
-	void Start()
-	{
-		lastAgentHit = -1;
-	}
+    // Use this for initialization
+    void Start()
+    {
+        lastAgentHit = -1;
+    }
-	private void OnTriggerExit(Collider other)
-	{
-		TennisArea area = areaObject.GetComponent<TennisArea>();
-		TennisAgent agentA = area.agentA.GetComponent<TennisAgent>();
-		TennisAgent agentB = area.agentB.GetComponent<TennisAgent>();
+    private void OnTriggerExit(Collider other)
+    {
+        TennisArea area = areaObject.GetComponent<TennisArea>();
+        TennisAgent agentA = area.agentA.GetComponent<TennisAgent>();
+        TennisAgent agentB = area.agentB.GetComponent<TennisAgent>();
-		if (other.name == "over")
-		{
-			if (lastAgentHit == 0)
-			{
+        if (other.name == "over")
+        {
+            if (lastAgentHit == 0)
+            {
-			}
-			else
-			{
+            }
+            else
+            {
-			}
-			lastAgentHit = 0;
+            }
+            lastAgentHit = 0;
-		}
-	}
+        }
+    }
-	private void OnCollisionEnter(Collision collision)
-	{
-		TennisArea area = areaObject.GetComponent<TennisArea>();
-		TennisAgent agentA = area.agentA.GetComponent<TennisAgent>();
-		TennisAgent agentB = area.agentB.GetComponent<TennisAgent>();
+    private void OnCollisionEnter(Collision collision)
+    {
+        TennisArea area = areaObject.GetComponent<TennisArea>();
+        TennisAgent agentA = area.agentA.GetComponent<TennisAgent>();
+        TennisAgent agentB = area.agentB.GetComponent<TennisAgent>();
-		if (collision.gameObject.tag == "iWall")
-		{
-			if (collision.gameObject.name == "wallA")
-			{
-				if (lastAgentHit == 0)
-				{
+        if (collision.gameObject.tag == "iWall")
+        {
+            if (collision.gameObject.name == "wallA")
+            {
+                if (lastAgentHit == 0)
+                {
-					agentB.score += 1;
-				}
-				else
-				{
-					agentA.SetReward(0);
+                    agentB.score += 1;
+                }
+                else
+                {
+                    agentA.SetReward(0);
-					agentA.score += 1;
-				}
-			}
-			else if (collision.gameObject.name == "wallB")
-			{
-				if (lastAgentHit == 0)
-				{
+                    agentA.score += 1;
+                }
+            }
+            else if (collision.gameObject.name == "wallB")
+            {
+                if (lastAgentHit == 0)
+                {
-					agentB.score += 1;
-				}
-				else
-				{
-					agentA.SetReward(0);
+                    agentB.score += 1;
+                }
+                else
+                {
+                    agentA.SetReward(0);
-					agentA.score += 1;
-				}
-			}
-			else if (collision.gameObject.name == "floorA")
-			{
-				if (lastAgentHit == 0 || lastAgentHit == -1)
-				{
+                    agentA.score += 1;
+                }
+            }
+            else if (collision.gameObject.name == "floorA")
+            {
+                if (lastAgentHit == 0 || lastAgentHit == -1)
+                {
-					agentB.SetReward(0);
-					agentB.score += 1;
-				}
-				else
-				{
+                    agentB.SetReward(0);
+                    agentB.score += 1;
+                }
+                else
+                {
-					agentB.SetReward(0);
-					agentB.score += 1;
+                    agentB.SetReward(0);
+                    agentB.score += 1;
-				}
-			}
-			else if (collision.gameObject.name == "floorB")
-			{
-				if (lastAgentHit == 1 || lastAgentHit == -1)
-				{
-					agentA.SetReward(0);
+                }
+            }
+            else if (collision.gameObject.name == "floorB")
+            {
+                if (lastAgentHit == 1 || lastAgentHit == -1)
+                {
+                    agentA.SetReward(0);
-					agentA.score += 1;
-				}
-				else
-				{
-					agentA.SetReward(0);
+                    agentA.score += 1;
+                }
+                else
+                {
+                    agentA.SetReward(0);
-					agentA.score += 1;
-				}
-			}
-			else if (collision.gameObject.name == "net")
-			{
-				if (lastAgentHit == 0)
-				{
+                    agentA.score += 1;
+                }
+            }
+            else if (collision.gameObject.name == "net")
+            {
+                if (lastAgentHit == 0)
+                {
-					agentB.SetReward(0);
-					agentB.score += 1;
-				}
-				else
-				{
-					agentA.SetReward(0);
+                    agentB.SetReward(0);
+                    agentB.score += 1;
+                }
+                else
+                {
+                    agentA.SetReward(0);
-					agentA.score += 1;
-				}
-			}
+                    agentA.score += 1;
+                }
+            }
-			agentB.Done();
-			area.MatchReset();
-		}
+            agentB.Done();
+            area.MatchReset();
+        }
-		if (collision.gameObject.tag == "agent")
-		{
-			if (collision.gameObject.name == "AgentA")
-			{
-				lastAgentHit = 0;
-			}
-			else
-			{
-				lastAgentHit = 1;
-			}
-		}
-	}
+        if (collision.gameObject.tag == "agent")
+        {
+            if (collision.gameObject.name == "AgentA")
+            {
+                lastAgentHit = 0;
+            }
+            else
+            {
+                lastAgentHit = 1;
+            }
+        }
+    }
 }

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

 
     /// Environment specific initialization.
     /**
-	* Implemented in environment-specific child class. 
-	* This method is called once when the environment is loaded.
-	*/
+    * Implemented in environment-specific child class. 
+    * This method is called once when the environment is loaded.
+    */
     public virtual void InitializeAcademy()
     {
 
 
     /// Environment specific step logic.
     /**
-	 * Implemented in environment-specific child class. 
-	 * This method is called at every step. 
-	*/
+     * Implemented in environment-specific child class. 
+     * This method is called at every step. 
+    */
     public virtual void AcademyStep()
     {
 
     /**
-	* Implemented in environment-specific child class. 
-	* This method is called everytime the Academy resets (when the global done
-	* flag is set to true).
-	*/
+    * Implemented in environment-specific child class. 
+    * This method is called everytime the Academy resets (when the global done
+    * flag is set to true).
+    */
     public virtual void AcademyReset()
     {
 

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

     /// <summary>
     /// The brain that will control this agent. 
     /// Use the inspector to drag the desired brain gameObject into
-	/// the Brain field.
+    /// the Brain field.
     ///</summary>
     [HideInInspector]
     public Brain brain;
     ///</summary>
     private float reward;
 
-    /// Whether or not the agent is requests an action
+    /// Whether or not the agent requests an action.
-    /// Whether or not the agent is requests a decision
+    /// Whether or not the agent requests a decision.
     private bool requestDecision;
 
     /// <summary> 
     private int id;
 
     /// <summary>
-    /// Unity method called when the agent is istanciated or set to active.
+    /// Unity method called when the agent is instantiated or set to active.
     /// </summary>
     private void OnEnable()
     {
     /// When GiveBrain is called, the agent unsubscribes from its 
     /// previous brain and subscribes to the one passed in argument.
     /// Use this method to provide a brain to the agent via script. 
-	///<param name= "b" >The Brain the agent will subscribe to.</param>
+    ///<param name= "b" >The Brain the agent will subscribe to.</param>
     /// <summary>
     public void GiveBrain(Brain b)
     {
     /// <summary>
     /// Is called when the agent must request the brain for a new decision.
     /// </summary>
-	public void RequestDecision()
+    public void RequestDecision()
     {
         requestDecision = true;
         RequestAction();
     /// </summary>
-	public void RequestAction()
+    public void RequestAction()
     {
         requestAction = true;
     }
     /// <summary>
     /// Initialize the agent with this method
     /// Must be implemented in agent-specific child class.
-	/// This method called only once when the agent is enabled.
+    /// This method called only once when the agent is enabled.
     /// </summary>
     public virtual void InitializeAgent()
     {
                 {
                     if (!hasAlreadyReset)
                     {
-                        //If event based, the agent can reset as soon
+                        // If event based, the agent can reset as soon
                         // as it is done
                         _AgentReset();
                         hasAlreadyReset = true;

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

     public KeyCode recordKey = KeyCode.R;
     public KeyCode resetKey = KeyCode.C;
 
-	// Use this for initialization
-	void Start () {
+    // Use this for initialization
+    void Start () {
-	}
-	
-	// Update is called once per frame
-	void Update () {
+    }
+    
+    // Update is called once per frame
+    void Update () {
         if (Input.GetKeyDown(recordKey))
         {
             recordExperiences = !recordExperiences;
         Monitor.Log("Recording experiences " + recordKey.ToString(), recordExperiences.ToString());
         float timeSinceBufferReset = Time.time - bufferResetTime;
         Monitor.Log("Seconds since buffer reset " + resetKey.ToString(), Mathf.FloorToInt(timeSinceBufferReset));
-	}
+    }
 
     void FixedUpdate()
     {

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

 
     //[HideInInspector]
     ///**<  \brief Keeps track of the agents which subscribe to this brain*/
-    //public Dictionary<int, Agent> agents = new Dictionary<int, Agent>();
+    // public Dictionary<int, Agent> agents = new Dictionary<int, Agent>();
 
     [SerializeField]
     ScriptableObject[] CoreBrains;
 
-    //Ensures the coreBrains are not dupplicated with the brains
+    // Ensures the coreBrains are not dupplicated with the brains
-	 * If the brain gameObject was just created, it generates a list of 
-	 * coreBrains (one for each brainType) */
+     * If the brain gameObject was just created, it generates a list of 
+     * coreBrains (one for each brainType) */
     public void UpdateCoreBrains()
     {
 

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

     public string logPath;
 
     /**< \brief The default reset parameters are sent via socket*/
-	public Dictionary<string, float> resetParameters;
+    public Dictionary<string, float> resetParameters;
 
     /**< \brief A list of the all the brains names sent via socket*/
     public List<string> brainNames;

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

     /// Uses the Decision Component to decide that action to take
     public void DecideAction(Dictionary<Agent, AgentInfo> agentInfo)
     {
-	    if (coord!=null)
-	    {
+        if (coord!=null)
+        {
-	    }
-		if (decision == null)
+        }
+
+        if (decision == null)
-
-			agent.UpdateVectorAction(decision.Decide(
+            agent.UpdateVectorAction(decision.Decide(
                 agentInfo[agent].stackedVectorObservation,
                 agentInfo[agent].visualObservations,
                 agentInfo[agent].reward,
         }
+
-				agentInfo[agent].stackedVectorObservation,
-				agentInfo[agent].visualObservations,
-				agentInfo[agent].reward,
-				agentInfo[agent].done,
-				agentInfo[agent].memories));
+                agentInfo[agent].stackedVectorObservation,
+                agentInfo[agent].visualObservations,
+                agentInfo[agent].reward,
+                agentInfo[agent].done,
+                agentInfo[agent].memories));
         }
     }
 
-#if UNITY_EDITOR
-        EditorGUILayout.LabelField("", GUI.skin.horizontalSlider);
-		broadcast = EditorGUILayout.Toggle(new GUIContent("Broadcast",
-					  "If checked, the brain will broadcast states and actions to Python."), broadcast);
-        if (brain.gameObject.GetComponent<Decision>() == null)
-        {
+        #if UNITY_EDITOR
+            EditorGUILayout.LabelField("", GUI.skin.horizontalSlider);
+            broadcast = EditorGUILayout.Toggle(new GUIContent("Broadcast",
+            "If checked, the brain will broadcast states and actions to Python."), broadcast);
+            if (brain.gameObject.GetComponent<Decision>() == null)
+            {
-        }
-#endif
+            }
+        #endif
     }
 
 }

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

     {
 #if ENABLE_TENSORFLOW
 #if UNITY_ANDROID
-		// This needs to ba called only once and will raise an exception if 
+        // This needs to ba called only once and will raise an exception if 
-		try{
-			TensorFlowSharp.Android.NativeBinding.Init();
-		}
-		catch{
-			
-		}
+        try{
+            TensorFlowSharp.Android.NativeBinding.Init();
+        }
+        catch{
+            
+        }
 #endif
         if ((communicator == null)
         || (!broadcast))
     public void DecideAction(Dictionary<Agent, AgentInfo> agentInfo)
     {
 #if ENABLE_TENSORFLOW
-		if (coord != null)
-		{
-			coord.GiveBrainInfo(brain, agentInfo);
-		}
+        if (coord != null)
+        {
+            coord.GiveBrainInfo(brain, agentInfo);
+        }
         int currentBatchSize = agentInfo.Count();
         List<Agent> agentList = agentInfo.Keys.ToList();
         if (currentBatchSize == 0)

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

         else
         {
             foreach (Agent agent in agentInfo.Keys)
-			{
+            {
                 var action = new float[1] { defaultAction };
                 foreach (DiscretePlayerAction dha in discretePlayerActions)
                 {

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

     /// \brief Implement this method to define the logic of decision making 
     /// for the CoreBrainHeuristic
     /** Given the information about the agent, return a vector of actions.
-	* @param state The state of the agent
-	* @param observation The cameras the agent uses
-	* @param reward The reward the agent had at the previous step
-	* @param done Weather or not the agent is done
-	* @param memory The memories stored from the previous step with MakeMemory()
-	* @return The vector of actions the agent will take at the next step
-	*/
+    * @param state The state of the agent
+    * @param observation The cameras the agent uses
+    * @param reward The reward the agent had at the previous step
+    * @param done Whether or not the agent is done
+    * @param memory The memories stored from the previous step with MakeMemory()
+    * @return The vector of actions the agent will take at the next step
+    */
-	* @param state The state of the agent
-	* @param observation The cameras the agent uses
-	* @param reward The reward the agent had at the previous step
-	* @param done Weather or not the agent is done
-	* @param memory The memories stored from the previous step with MakeMemory()
-	* @return The vector of memories the agent will use at the next step
-	*/
+    * @param state The state of the agent
+    * @param observation The cameras the agent uses
+    * @param reward The reward the agent had at the previous step
+    * @param done Weather or not the agent is done
+    * @param memory The memories stored from the previous step with MakeMemory()
+    * @return The vector of memories the agent will use at the next step
+    */
     List<float> MakeMemory(List<float> state, List<Texture2D> observation, float reward, bool done, List<float> memory);
 }

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

         sMessage.maxes= new List<bool>(defaultNumAgents);
         sMessage.textObservations = new List<string>(defaultNumAgents);
 
-        //Initialize the list of brains the Communicator must listen to
+        // Initialize the list of brains the Communicator must listen to
         // Issue : This assumes all brains are broadcasting.
         foreach(string k in accParamerters.brainNames){
             current_agents[k] = new List<Agent>(defaultNumAgents);
         return triedSendState;
     }
 
-	public Dictionary<string, bool> GetSent()
-	{
+    public Dictionary<string, bool> GetSent()
+    {
-	}
+    }
 
     /// Listens for actions, memories, and values and sends them 
     /// to the corrensponding brains.

unity-environment/Assets/ML-Agents/Template/Scripts/TemplateAcademy.cs

 
 public class TemplateAcademy : Academy {
 
-	public override void AcademyReset()
-	{
+    public override void AcademyReset()
+    {
-	}
+    }
-	public override void AcademyStep()
-	{
+    public override void AcademyStep()
+    {
-	}
+    }
 
 }

unity-environment/Assets/ML-Agents/Template/Scripts/TemplateAgent.cs

 
 
 
-	public override void CollectObservations()
-	{
+    public override void CollectObservations()
+    {
-	}
+    }
-	}
+    }
-	public override void AgentReset()
-	{
+    public override void AgentReset()
+    {
-	}
+    }
-	public override void AgentOnDone()
-	{
+    public override void AgentOnDone()
+    {
-	}
+    }
 }

unity-environment/Assets/ML-Agents/Template/Scripts/TemplateDecision.cs

     public List<float> MakeMemory(List<float> state, List<Texture2D> observation, float reward, bool done, List<float> memory)
     {
         return new List<float>();
-		
+        
     }
 }