Added tooltip and helpURL to ML-Agents scripts (#276)

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

 [System.Serializable]
 public class ScreenConfiguration
 {
+    [Tooltip("Width of the environment window in pixels.")]
+    [Tooltip("Height of the environment window in pixels")]
+    [Tooltip("Rendering quality of environment. (Higher is better quality)")]
+    [Tooltip("Speed at which environment is run. (Higher is faster)")]
+    [Tooltip("FPS engine attempts to maintain.")]
     public int targetFrameRate;
 
     public ScreenConfiguration(int w, int h, int q, float ts, int tf)
 }
 
 
+[HelpURL("https://github.com/Unity-Technologies/ml-agents/blob/master/docs/Agents-Editor-Interface.md#academy")]
 /** Create a child class to implement InitializeAcademy(), AcademyStep() 
  * and AcademyReset(). The child class script must be attached to an empty game
  * object in your scene, and there can only be one such object within the scene.
 
 
     [SerializeField]
+    [Tooltip("Total number of steps per episode. \n" +
+             "0 corresponds to episodes without a maximum number of steps. \n" +
+             "Once the step counter reaches maximum, the environment will reset.")]
+    [Tooltip("How many steps of the environment to skip before asking Brains for decisions.")]
+    [Tooltip("How many seconds to wait between steps when running in Inference.")]
     private float waitTime;
     [HideInInspector]
     public bool isInference = true;
     [SerializeField]
+    [Tooltip("The engine-level settings which correspond to rendering quality and engine speed during Training.")]
+    [Tooltip("The engine-level settings which correspond to rendering quality and engine speed during Inference.")]
+    [Tooltip("List of custom parameters that can be changed in the environment on reset.")]
     private ResetParameter[] defaultResetParameters;
 
     /**< \brief Contains a mapping from parameter names to float values. */

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

 using UnityEngine;
 
 
+[HelpURL("https://github.com/Unity-Technologies/ml-agents/blob/master/docs/Agents-Editor-Interface.md#agent")]
 /** Generic functions for parent Agent class.
  * Contains all logic for Brain-Agent communication and Agent-Environment 
  * interaction.
+    [Tooltip("The brain to register this agent to. Can be dragged into the inspector using the Editor.")]
+    [Tooltip("A list of Cameras which will be used to generate observations.")]
+    [Tooltip("The per-agent maximum number of steps.")]
     /**<  \brief  The number of steps the agent takes before being done. */
     /**< If set to 0, the agent can only be set to done via a script.
     * If set to any positive integer, the agent will be set to done after that
+    [Tooltip("If checked, the agent will reset on done. Else, AgentOnDone() will be called.")]
     /**<  \brief Determines the behaviour of the Agent when done.*/
     /**< If true, the agent will reset when done. 
 	 * If not, the agent will remain done, and no longer take actions.*/

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

 [System.Serializable]
 public class BrainParameters
 {
+    [Tooltip("Length of state vector for brain (In Continuous state space)." +
+             "Or number of possible values (in Discrete state space).")]
+    [Tooltip("Number of states that will be staked before beeing fed to the neural network.")]
+    [Tooltip("Length of action vector for brain (In Continuous state space)." +
+             "Or number of possible values (in Discrete action space).")]
+    [Tooltip("Length of memory vector for brain. Used with Recurrent networks.")]
+    [Tooltip("Describes height, width, and whether to greyscale visual observations for the Brain.")]
-
-    public string[] actionDescriptions;
+    [Tooltip("A list of strings used to name the available actions for the Brain.")]
+	public string[] actionDescriptions;
+    [Tooltip("Corresponds to whether state vector contains a single integer (Discrete) " +
+             "or a series of real-valued floats (Continuous).")]
+    [Tooltip("Corresponds to whether action vector contains a single integer (Discrete)" +
+             " or a series of real-valued floats (Continuous).")]
+[HelpURL("https://github.com/Unity-Technologies/ml-agents/blob/master/docs/Agents-Editor-Interface.md#brain")]
 /**
  * Contains all high-level Brain logic. 
  * Add this component to an empty GameObject in your scene and drag this 
     public Dictionary<int, float[]> currentActions = new Dictionary<int, float[]>(32);
     public Dictionary<int, float[]> currentMemories = new Dictionary<int, float[]>(32);
 
+	[Tooltip("Define state, observation, and action spaces for the Brain.")]
-    /**<  \brief Defines what is the type of the brain : 
+
+	/**<  \brief Defines what is the type of the brain : 
+	[Tooltip("Describes how the Brain will decide actions.")]
     public BrainType brainType;
 
     [HideInInspector]

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

     {
 #if UNITY_EDITOR
         EditorGUILayout.LabelField("", GUI.skin.horizontalSlider);
-        broadcast = EditorGUILayout.Toggle("Broadcast", broadcast);
+		broadcast = EditorGUILayout.Toggle(new GUIContent("Broadcast",
+					  "If checked, the brain will broadcast states and actions to Python."), broadcast);
         if (brain.gameObject.GetComponent<Decision>() == null)
         {
             EditorGUILayout.HelpBox("You need to add a 'Decision' component to this gameObject", MessageType.Error);

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

 {
 
     [SerializeField]
+    [Tooltip("If checked, the brain will broadcast states and actions to Python.")]
     private bool broadcast = true;
 
     [System.Serializable]
 
     ExternalCommunicator coord;
 
+    [Tooltip("This must be the bytes file corresponding to the pretrained Tensorflow graph.")]
+
+    [Tooltip("If your graph takes additional inputs that are fixed (example: noise level) you can specify them here.")]
     ///  Modify only in inspector : If your graph takes additional inputs that are fixed you can specify them here.
     private TensorFlowAgentPlaceholder[] graphPlaceholders;
     ///  Modify only in inspector : Name of the placholder of the batch size
     {
 #if ENABLE_TENSORFLOW && UNITY_EDITOR
         EditorGUILayout.LabelField("", GUI.skin.horizontalSlider);
-        broadcast = EditorGUILayout.Toggle("Broadcast", broadcast);
+        broadcast = EditorGUILayout.Toggle(new GUIContent("Broadcast",
+                      "If checked, the brain will broadcast states and actions to Python."), broadcast);
         var serializedBrain = new SerializedObject(this);
         GUILayout.Label("Edit the Tensorflow graph parameters here");
         var tfGraphModel = serializedBrain.FindProperty("graphModel");
         }
 
 
-        graphScope = EditorGUILayout.TextField("Graph Scope : ", graphScope);
+        graphScope = EditorGUILayout.TextField(new GUIContent("Graph Scope", "If you set a scope while training your tensorflow model, " +
+                           "all your placeholder name will have a prefix. You must specify that prefix here."), graphScope);
-        BatchSizePlaceholderName = EditorGUILayout.TextField("Batch Size Node Name", BatchSizePlaceholderName);
+        BatchSizePlaceholderName = EditorGUILayout.TextField(new GUIContent("Batch Size Node Name", "If the batch size is one of " +
+                            "the inputs of your graph, you must specify the name if the placeholder here."), BatchSizePlaceholderName);
-        StatePlacholderName = EditorGUILayout.TextField("State Node Name", StatePlacholderName);
+        StatePlacholderName = EditorGUILayout.TextField(new GUIContent("State Node Name", "If your graph uses the state as an input, " +
+                            "you must specify the name if the placeholder here."), StatePlacholderName);
-        RecurrentInPlaceholderName = EditorGUILayout.TextField("Recurrent Input Node Name", RecurrentInPlaceholderName);
+        RecurrentInPlaceholderName = EditorGUILayout.TextField(new GUIContent("Recurrent Input Node Name", "If your graph uses a " +
+                          "recurrent input / memory as input and outputs new recurrent input / memory, " +
+                          "you must specify the name if the input placeholder here."), RecurrentInPlaceholderName);
-        RecurrentOutPlaceholderName = EditorGUILayout.TextField("Recurrent Output Node Name", RecurrentOutPlaceholderName);
+        RecurrentOutPlaceholderName = EditorGUILayout.TextField(new GUIContent("Recurrent Output Node Name", " If your graph uses a " +
+                           "recurrent input / memory as input and outputs new recurrent input / memory, you must specify the name if " +
+                           "the output placeholder here."), RecurrentOutPlaceholderName);
 
         if (brain.brainParameters.cameraResolutions != null)
         {
         {
             ActionPlaceholderName = "action";
         }
-        ActionPlaceholderName = EditorGUILayout.TextField("Action Node Name", ActionPlaceholderName);
+        ActionPlaceholderName = EditorGUILayout.TextField(new GUIContent("Action Node Name", "Specify the name of the " +
+                         "placeholder corresponding to the actions of the brain in your graph. If the action space type is " +
+                         "continuous, the output must be a one dimensional tensor of float of length Action Space Size, " +
+                         "if the action space type is discrete, the output must be a one dimensional tensor of int " +
+                         "of length 1."), ActionPlaceholderName);
 
 
 

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

     ExternalCommunicator coord;
 
     [SerializeField]
+    [Tooltip("The list of keys and the value they correspond to for continuous control.")]
+	[Tooltip("The list of keys and the value they correspond to for discrete control.")]
     /// Contains the mapping from input to discrete actions
     private DiscretePlayerAction[] discretePlayerActions;
     [SerializeField]
     {
 #if UNITY_EDITOR
         EditorGUILayout.LabelField("", GUI.skin.horizontalSlider);
-        broadcast = EditorGUILayout.Toggle("Broadcast", broadcast);
+		broadcast = EditorGUILayout.Toggle(new GUIContent("Broadcast",
+					  "If checked, the brain will broadcast states and actions to Python."), broadcast);
         var serializedBrain = new SerializedObject(this);
         if (brain.brainParameters.actionSpaceType == StateType.continuous)
         {