Brains as Scriptable Objects (#1250)

* Initial Commit
Ported most functionalities, still need to :
 - Documentation
 - Add Comments
 - Custom drawer for BrainParameters
 - Fix the UnitTests
 - Review Functionalities

* Added Custom Drawer for the Brain Parameters

* Improvements to the HubDrawer

* Modified the Brain Editors

* Minor bug fixes and UI changes

* Modified the Help Boxes of the Drawers

* Modified Brain class, renamed Initialize and made DecideAction virtual

* Fix the UnityTests

* Simpler Brain creation menu

* Renamed Internal Brain to Learning Brain

* modified the parameters to remove reference to External or Internal in the Protobuf objects

* Updated the protobuf generated files

* Fix the Pytests

* Removed the graph scope from the Learning Brain

* cleaner logic than try catch

* Removed the isExternal field of the brain and put the isTraining logic into LearningBrain and Training Hub

* Modified how the Brain finds the A...

UnitySDK/Assets/ML-Agents/Editor/BrainEditor.cs

 
 namespace MLAgents
 {
-/*
- This code is meant to modify the behavior of the inspector on Brain Components.
- Depending on the type of brain that is used, the available fields will be modified in the inspector accordingly.
-*/
+    /// <summary>
+    /// CustomEditor for the Brain base class. Defines the default Inspector view for a Brain.
+    /// Shows the BrainParameters of the Brain and expose a tool to deep copy BrainParameters
+    /// between brains.
+    /// </summary>
-    {
-        [SerializeField] bool _Foldout = true;
-
+    {        
-            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);
-            }
-
-            serializedBrain.Update();
-
-
-            _Foldout = EditorGUILayout.Foldout(_Foldout, "Brain Parameters");
-            int indentLevel = EditorGUI.indentLevel;
-            if (_Foldout)
-            {
-                EditorGUI.indentLevel++;
-                EditorGUILayout.LabelField("Vector Observation");
-                EditorGUI.indentLevel++;
-
-                SerializedProperty bpVectorObsSize =
-                    serializedBrain.FindProperty("brainParameters.vectorObservationSize");
-                EditorGUILayout.PropertyField(bpVectorObsSize, new GUIContent("Space Size",
-                    "Length of state " +
-                    "vector for brain (In Continuous state space)." +
-                    "Or number of possible values (in Discrete state space)."));
-
-
-                SerializedProperty bpNumStackedVectorObs =
-                    serializedBrain.FindProperty("brainParameters.numStackedVectorObservations");
-                EditorGUILayout.PropertyField(bpNumStackedVectorObs, new GUIContent(
-                    "Stacked Vectors", "Number of states that" +
-                                       " will be stacked before beeing fed to the neural network."));
-
-                EditorGUI.indentLevel--;
-                SerializedProperty bpCamResol =
-                    serializedBrain.FindProperty("brainParameters.cameraResolutions");
-                EditorGUILayout.PropertyField(bpCamResol, new GUIContent("Visual Observation",
-                    "Describes height, " +
-                    "width, and whether to greyscale visual observations for the Brain."), true);
-
-                EditorGUILayout.LabelField("Vector Action");
-                EditorGUI.indentLevel++;
-
-                SerializedProperty bpVectorActionType =
-                    serializedBrain.FindProperty("brainParameters.vectorActionSpaceType");
-                EditorGUILayout.PropertyField(bpVectorActionType, new GUIContent("Space Type",
-                    "Corresponds to whether state" +
-                    " vector contains a single integer (Discrete) " +
-                    "or a series of real-valued floats (Continuous)."));
-                if (bpVectorActionType.enumValueIndex == 1)
-                {
-                    //Continuous case :
-                    SerializedProperty bpVectorActionSize =
-                        serializedBrain.FindProperty("brainParameters.vectorActionSize");
-                    bpVectorActionSize.arraySize = 1;
-                    SerializedProperty continuousActionSize =
-                        bpVectorActionSize.GetArrayElementAtIndex(0);
-                    EditorGUILayout.PropertyField(continuousActionSize, new GUIContent(
-                        "Space Size", "Length of continuous action vector."));
-                    
-                }
-                else
-                {
-                    // Discrete case :
-                    SerializedProperty bpVectorActionSize =
-                        serializedBrain.FindProperty("brainParameters.vectorActionSize");
-                    bpVectorActionSize.arraySize = EditorGUILayout.IntField(
-                        "Branches Size", bpVectorActionSize.arraySize);
-                    EditorGUI.indentLevel++;
-                    for (int branchIndex = 0;
-                        branchIndex < bpVectorActionSize.arraySize;
-                        branchIndex++)
-                    {
-                        SerializedProperty branchActionSize =
-                            bpVectorActionSize.GetArrayElementAtIndex(branchIndex);
-                        EditorGUILayout.PropertyField(branchActionSize, new GUIContent(
-                            "Branch " + branchIndex+" Size", 
-                            "Number of possible actions for the branch number " + branchIndex+"."));
-                    }
-                    EditorGUI.indentLevel--;
-
-                }
-
-                try
-                {
-                    BrainParameters parameters = myBrain.brainParameters;
-                    int numberOfDescriptions = 0;
-                    if (parameters.vectorActionSpaceType == SpaceType.continuous)
-                        numberOfDescriptions = parameters.vectorActionSize[0];
-                    else
-                        numberOfDescriptions = parameters.vectorActionSize.Length;
-                    if (parameters.vectorActionDescriptions == null ||
-                        parameters.vectorActionDescriptions.Length != numberOfDescriptions)
-                        parameters.vectorActionDescriptions = new string[numberOfDescriptions];
-                }
-                catch
-                {
-
-                }
-
-                if (bpVectorActionType.enumValueIndex == 1)
-                {
-                    //Continuous case :
-                    SerializedProperty bpVectorActionDescription =
-                        serializedBrain.FindProperty("brainParameters.vectorActionDescriptions");
-                    EditorGUILayout.PropertyField(bpVectorActionDescription, new GUIContent(
-                        "Action Descriptions", "A list of strings used to name" +
-                                               " the available actions for the Brain."), true);
-                }
-                else
-                {
-                    // Discrete case :
-                    SerializedProperty bpVectorActionDescription =
-                        serializedBrain.FindProperty("brainParameters.vectorActionDescriptions");
-                    EditorGUILayout.PropertyField(bpVectorActionDescription, new GUIContent(
-                        "Branch Descriptions", "A list of strings used to name" +
-                                               " the available branches for the Brain."), true);
-                }
-            }
-
-            EditorGUI.indentLevel = indentLevel;
-            SerializedProperty bt = serializedBrain.FindProperty("brainType");
-            EditorGUILayout.PropertyField(bt);
-
-            if (bt.enumValueIndex < 0)
+            var brain = (Brain) target;
+            var brainToCopy = EditorGUILayout.ObjectField(
+                "Copy Brain Parameters from : ", null, typeof(Brain), false) as Brain;
+            if (brainToCopy != null)
-                bt.enumValueIndex = (int) BrainType.Player;
+                brain.brainParameters = brainToCopy.brainParameters.Clone();
-
+            var serializedBrain = serializedObject;
+            serializedBrain.Update(); 
+            EditorGUILayout.PropertyField(serializedBrain.FindProperty("brainParameters"), true);
-
-            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
+            
+            // Draws a horizontal thick line
+            EditorGUILayout.LabelField("", GUI.skin.horizontalSlider);
-}
+}

UnitySDK/Assets/ML-Agents/Editor/BrainEditor.cs.meta

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+timeCreated: 1537834304

UnitySDK/Assets/ML-Agents/Editor/ResetParameterDrawer.cs

 
 namespace MLAgents
 {
-
+    /// <summary>
+    /// PropertyDrawer for ResetParameters. Defines how ResetParameters are displayed in the
+    /// Inspector.
+    /// </summary>
-        private ResetParameters _Dictionary;
-        private const float lineHeight = 17f;
+        private ResetParameters _parameters;
+        // The height of a line in the Unity Inspectors
+        private const float LineHeight = 17f;
+        // This is the prefix for the key when you add a reset parameter
+        private const string NewKeyPrefix = "Param-";
+        /// <summary>
+        /// Computes the height of the Drawer depending on the property it is showing
+        /// </summary>
+        /// <param name="property">The property that is being drawn.</param>
+        /// <param name="label">The label of the property being drawn.</param>
+        /// <returns>The vertical space needed to draw the property.</returns>
-            CheckInitialize(property, label);
-            return (_Dictionary.Count + 2) * lineHeight;
+            LazyInitializeParameters(property, label);
+            return (_parameters.Count + 2) * LineHeight;
+        /// <inheritdoc />
-
-            CheckInitialize(property, label);
-            position.height = lineHeight;
+            LazyInitializeParameters(property, label);
+            position.height = LineHeight;
-
+            position.y += LineHeight;
+            var width = position.width / 2 - 24;
+            var keyRect = new Rect(position.x + 20, position.y, width, position.height);
+            var valueRect = new Rect(position.x + width + 30, position.y, width, position.height);
+            DrawAddRemoveButtons(keyRect, valueRect);
-            foreach (var item in _Dictionary)
+            foreach (var parameter in _parameters)
-                var key = item.Key;
-                var value = item.Value;
-                position.y += lineHeight;
-
-                // This is the rectangle for the key
-                var keyRect = position;
-                keyRect.x += 20;
-                keyRect.width /= 2;
-                keyRect.width -= 24;
+                var key = parameter.Key;
+                var value = parameter.Value;
+                keyRect.y += LineHeight;
+                valueRect.y += LineHeight;
-                    EditorSceneManager.MarkSceneDirty(EditorSceneManager.GetActiveScene());
+                    MarkSceneAsDirty();
-                        _Dictionary.Remove(key);
-                        _Dictionary.Add(newKey, value);
+                        _parameters.Remove(key);
+                        _parameters.Add(newKey, value);
-
-                // This is the Rectangle for the value
-                var valueRect = position;
-                valueRect.x = position.width / 2 + 15;
-                valueRect.width = keyRect.width - 18;
-                    EditorSceneManager.MarkSceneDirty(EditorSceneManager.GetActiveScene());
-                    _Dictionary[key] = value;
+                    MarkSceneAsDirty();
+                    _parameters[key] = value;
+            EditorGUI.EndProperty();
+        }
-            // This is the rectangle for the Add button
-            position.y += lineHeight;
-            var AddButtonRect = position;
-            AddButtonRect.x += 20;
-            AddButtonRect.width /= 2;
-            AddButtonRect.width -= 24;
-            if (GUI.Button(AddButtonRect, new GUIContent("Add New",
-                "Add a new item to the default reset paramters"), EditorStyles.miniButton))
+        /// <summary>
+        /// Draws the Add and Remove buttons.
+        /// </summary>
+        /// <param name="addRect">The rectangle for the Add New button.</param>
+        /// <param name="removeRect">The rectangle for the Remove Last button.</param>
+        private void DrawAddRemoveButtons(Rect addRect, Rect removeRect)
+        {
+            // This is the Add button
+            if (_parameters.Count == 0)
+            {
+                addRect.width *= 2;
+            }
+            if (GUI.Button(addRect,
+                new GUIContent("Add New", "Add a new item to the default reset parameters"), 
+                EditorStyles.miniButton))
+            {
+                MarkSceneAsDirty();
+                AddParameter();
+            }
+            
+            // If there are no items in the ResetParameters, Hide the Remove button
+            if (_parameters.Count == 0)
-                EditorSceneManager.MarkSceneDirty(EditorSceneManager.GetActiveScene());
-                AddNewItem();
+                return;
-
-            // This is the rectangle for the Remove button
-            var RemoveButtonRect = position;
-            RemoveButtonRect.x = position.width / 2 + 15;
-            RemoveButtonRect.width = AddButtonRect.width - 18;
-            if (GUI.Button(RemoveButtonRect, new GUIContent("Remove Last",
-                "Remove the last item to the default reset paramters"), EditorStyles.miniButton))
+            // This is the Remove button
+            if (GUI.Button(removeRect, 
+                new GUIContent(
+                    "Remove Last", "Remove the last item from the default reset parameters"), 
+                EditorStyles.miniButton))
-                EditorSceneManager.MarkSceneDirty(EditorSceneManager.GetActiveScene());
-                RemoveLastItem();
+                MarkSceneAsDirty();
+                RemoveLastParameter();
-
-
-            EditorGUI.EndProperty();
-
-        private void CheckInitialize(SerializedProperty property, GUIContent label)
+        /// <summary>
+        /// Signals that the property has been modified and requires the scene to be saved for
+        /// the changes to persist. Only works when the Editor is not playing.
+        /// </summary>
+        private static void MarkSceneAsDirty()
-            if (_Dictionary == null)
+            if (!EditorApplication.isPlaying)
-                var target = property.serializedObject.targetObject;
-                _Dictionary = fieldInfo.GetValue(target) as ResetParameters;
-                if (_Dictionary == null)
-                {
-                    _Dictionary = new ResetParameters();
-                    fieldInfo.SetValue(target, _Dictionary);
-                }
+                EditorSceneManager.MarkSceneDirty(EditorSceneManager.GetActiveScene());
-        private void ClearResetParamters()
+        /// <summary>
+        /// Ensures that the state of the Drawer is synchronized with the property.
+        /// </summary>
+        /// <param name="property">The SerializedProperty of the ResetParameters
+        /// to make the custom GUI for.</param>
+        /// <param name="label">The label of this property.</param>
+        private void LazyInitializeParameters(SerializedProperty property, GUIContent label)
-            _Dictionary.Clear();
+            if (_parameters != null)
+            {
+                return;
+            }
+            var target = property.serializedObject.targetObject;
+            _parameters = fieldInfo.GetValue(target) as ResetParameters;
+            if (_parameters == null)
+            {
+                _parameters = new ResetParameters();
+                fieldInfo.SetValue(target, _parameters);
+            }
-        private void RemoveLastItem()
+        /// <summary>
+        /// Removes the last ResetParameter from the ResetParameters
+        /// </summary>
+        private void RemoveLastParameter()
-            if (_Dictionary.Count > 0)
+            if (_parameters.Count > 0)
-                string key = _Dictionary.Keys.ToList()[_Dictionary.Count - 1];
-                _Dictionary.Remove(key);
+                string key = _parameters.Keys.ToList()[_parameters.Count - 1];
+                _parameters.Remove(key);
-        private void AddNewItem()
+        /// <summary>
+        /// Adds a new ResetParameter to the ResetParameters with a default name.
+        /// </summary>
+        private void AddParameter()
-            string key = "Param-" + _Dictionary.Count.ToString();
+            string key = NewKeyPrefix + _parameters.Count;
-                _Dictionary.Add(key, value);
+                _parameters.Add(key, value);
             }
             catch (Exception e)
             {

UnitySDK/Assets/ML-Agents/Editor/Tests/DemonstrationTests.cs

             {
                 vectorObservationSize = 3,
                 numStackedVectorObservations = 2,
-                cameraResolutions = new [] {new resolution()},
+                cameraResolutions = new [] {new Resolution()},
                 vectorActionDescriptions = new [] {"TestActionA", "TestActionB"},
                 vectorActionSize = new [] {2, 2},
                 vectorActionSpaceType = SpaceType.discrete

UnitySDK/Assets/ML-Agents/Editor/Tests/MLAgentsEditModeTest.cs

     // It is left empty because we are not testing any brain behavior
     public class TestBrain : Brain
     {
+        public int numberOfCallsToInitialize = 0;
+        public int numberOfCallsToDecideAction = 0;
+        public static TestBrain Instantiate()
+        {
+            return CreateInstance<TestBrain>();
+        }
+        protected override void Initialize()
+        {
+            numberOfCallsToInitialize++;
+        }
+
+        protected override void DecideAction()
+        {
+            base.DecideAction();
+            numberOfCallsToDecideAction++;
+            agentInfos.Clear();
+        }
     }
 
 
     public class EditModeTestInitialization
     {
 
+        private Brain GenerateTestBrain()
+        {
+            return ScriptableObject.CreateInstance<TestBrain>();
+        } 
+        
         [Test]
         public void TestAcademy()
         {
             GameObject acaGO = new GameObject("TestAcademy");
             acaGO.AddComponent<TestAcademy>();
             TestAcademy aca = acaGO.GetComponent<TestAcademy>();
-            GameObject brainGO = new GameObject("TestBrain");
-            brainGO.transform.parent = acaGO.transform;
-            brainGO.AddComponent<TestBrain>();
-            TestBrain brain = brainGO.GetComponent<TestBrain>();
+            TestBrain brain = TestBrain.Instantiate();
             brain.brainParameters = new BrainParameters();
             brain.brainParameters.vectorObservationSize = 0;
             agent1.GiveBrain(brain);
             GameObject acaGO = new GameObject("TestAcademy");
             acaGO.AddComponent<TestAcademy>();
             TestAcademy aca = acaGO.GetComponent<TestAcademy>();
-            GameObject brainGO = new GameObject("TestBrain");
-            brainGO.transform.parent = acaGO.transform;
-            brainGO.AddComponent<TestBrain>();
-            TestBrain brain = brainGO.GetComponent<TestBrain>();
+            TestBrain brain = TestBrain.Instantiate();
 
 
             MethodInfo AgentEnableMethod = typeof(Agent).GetMethod(
             agent2.agentParameters.onDemandDecision = true;
             // agent2 will request decisions only when RequestDecision is called
             brain.brainParameters.vectorObservationSize = 0;
-            brain.brainParameters.cameraResolutions = new resolution[0];
+            brain.brainParameters.cameraResolutions = new Resolution[0];
             agent1.GiveBrain(brain);
             agent2.GiveBrain(brain);
 
             GameObject acaGO = new GameObject("TestAcademy");
             acaGO.AddComponent<TestAcademy>();
             TestAcademy aca = acaGO.GetComponent<TestAcademy>();
-            GameObject brainGO = new GameObject("TestBrain");
-            brainGO.transform.parent = acaGO.transform;
-            brainGO.AddComponent<TestBrain>();
-            TestBrain brain = brainGO.GetComponent<TestBrain>();
+            TestBrain brain = TestBrain.Instantiate();
 
 
             MethodInfo AgentEnableMethod = typeof(Agent).GetMethod(
             agent2.agentParameters.onDemandDecision = true;
             // agent2 will request decisions only when RequestDecision is called
             brain.brainParameters.vectorObservationSize = 0;
-            brain.brainParameters.cameraResolutions = new resolution[0];
+            brain.brainParameters.cameraResolutions = new Resolution[0];
             agent1.GiveBrain(brain);
             agent2.GiveBrain(brain);
 
             GameObject acaGO = new GameObject("TestAcademy");
             acaGO.AddComponent<TestAcademy>();
             TestAcademy aca = acaGO.GetComponent<TestAcademy>();
-            GameObject brainGO = new GameObject("TestBrain");
-            brainGO.transform.parent = acaGO.transform;
-            brainGO.AddComponent<TestBrain>();
-            TestBrain brain = brainGO.GetComponent<TestBrain>();
+            TestBrain brain = TestBrain.Instantiate();
 
 
             MethodInfo AgentEnableMethod = typeof(Agent).GetMethod(
             agent1.agentParameters.maxStep = 20;
             agent2.agentParameters.maxStep = 30;
             brain.brainParameters.vectorObservationSize = 0;
-            brain.brainParameters.cameraResolutions = new resolution[0];
+            brain.brainParameters.cameraResolutions = new Resolution[0];
             agent1.GiveBrain(brain);
             agent2.GiveBrain(brain);
 
             GameObject acaGO = new GameObject("TestAcademy");
             acaGO.AddComponent<TestAcademy>();
             TestAcademy aca = acaGO.GetComponent<TestAcademy>();
-            GameObject brainGO = new GameObject("TestBrain");
-            brainGO.transform.parent = acaGO.transform;
-            brainGO.AddComponent<TestBrain>();
-            TestBrain brain = brainGO.GetComponent<TestBrain>();
+            TestBrain brain = TestBrain.Instantiate();
 
 
             MethodInfo AgentEnableMethod = typeof(Agent).GetMethod(
             agent1.agentParameters.resetOnDone = false;
             agent2.agentParameters.resetOnDone = false;
             brain.brainParameters.vectorObservationSize = 0;
-            brain.brainParameters.cameraResolutions = new resolution[0];
+            brain.brainParameters.cameraResolutions = new Resolution[0];
             agent1.GiveBrain(brain);
             agent2.GiveBrain(brain);
 
             GameObject acaGO = new GameObject("TestAcademy");
             acaGO.AddComponent<TestAcademy>();
             TestAcademy aca = acaGO.GetComponent<TestAcademy>();
-            GameObject brainGO = new GameObject("TestBrain");
-            brainGO.transform.parent = acaGO.transform;
-            brainGO.AddComponent<TestBrain>();
-            TestBrain brain = brainGO.GetComponent<TestBrain>();
+            TestBrain brain = TestBrain.Instantiate();
 
 
             MethodInfo AgentEnableMethod = typeof(Agent).GetMethod(
             // agent2 will request decisions only when RequestDecision is called
             agent1.agentParameters.maxStep = 20;
             brain.brainParameters.vectorObservationSize = 0;
-            brain.brainParameters.cameraResolutions = new resolution[0];
+            brain.brainParameters.cameraResolutions = new Resolution[0];
             agent1.GiveBrain(brain);
             agent2.GiveBrain(brain);
 

UnitySDK/Assets/ML-Agents/Examples/3DBall/Prefabs/Game.prefab

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+  brain: {fileID: 11400000, guid: 97d8f9d40dc8c452f932f7caa9549c7d, type: 2}
   agentParameters:
     agentCameras: []
     maxStep: 5000

UnitySDK/Assets/ML-Agents/Examples/3DBall/Scenes/3DBall.unity

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

 using UnityEngine;
 using MLAgents;
 
-public class Ball3DDecision : MonoBehaviour, Decision
+public class Ball3DDecision : Decision
-    public float[] Decide(
+    public override float[] Decide(
         List<float> vectorObs,
         List<Texture2D> visualObs,
         float reward,
-        if (gameObject.GetComponent<Brain>().brainParameters.vectorActionSpaceType
-            == SpaceType.continuous)
+        if (brainParameters.vectorActionSpaceType == SpaceType.continuous)
         {
             List<float> act = new List<float>();
 
         return new float[1] { 1f };
     }
 
-    public List<float> MakeMemory(
+    public override List<float> MakeMemory(
         List<float> vectorObs,
         List<Texture2D> visualObs,
         float reward,

UnitySDK/Assets/ML-Agents/Examples/Basic/Scripts/BasicDecision.cs

 using UnityEngine;
 using MLAgents;
 
-public class BasicDecision : MonoBehaviour, Decision
+public class BasicDecision : Decision
-    public float[] Decide(
+    public override float[] Decide(
         List<float> vectorObs,
         List<Texture2D> visualObs,
         float reward,
         return new float[1] { 1f };
     }
 
-    public List<float> MakeMemory(
+    public override List<float> MakeMemory(
         List<float> vectorObs,
         List<Texture2D> visualObs,
         float reward,

UnitySDK/Assets/ML-Agents/Examples/Reacher/Scripts/ReacherDecision.cs

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

UnitySDK/Assets/ML-Agents/Examples/SharedAssets/Scripts/RandomDecision.cs

 namespace MLAgents
 {
 
-    public class RandomDecision : MonoBehaviour, Decision
+    public class RandomDecision : Decision
-        BrainParameters brainParameters;
-        SpaceType actionSpaceType;
-        public void Awake()
-        {
-            brainParameters =
-                gameObject.GetComponent<Brain>().brainParameters;
-            actionSpaceType = brainParameters.vectorActionSpaceType;
-        }
-
-        public float[] Decide(
+        public override float[] Decide(
             List<float> vectorObs,
             List<Texture2D> visualObs,
             float reward,
-            if (actionSpaceType == SpaceType.continuous)
+            if (brainParameters.vectorActionSpaceType == SpaceType.continuous)
             {
                 List<float> act = new List<float>();
 
             }
         }
 
-        public List<float> MakeMemory(
+        public override List<float> MakeMemory(
             List<float> vectorObs,
             List<Texture2D> visualObs,
             float reward,

UnitySDK/Assets/ML-Agents/Examples/Template/Scripts/TemplateDecision.cs

 using UnityEngine;
 using MLAgents;
 
-public class TemplateDecision : MonoBehaviour, Decision
+public class TemplateDecision : Decision
-    public float[] Decide(
+    public override float[] Decide(
         List<float> vectorObs,
         List<Texture2D> visualObs,
         float reward,
         return new float[0];
     }
 
-    public List<float> MakeMemory(
+    public override List<float> MakeMemory(
         List<float> vectorObs,
         List<Texture2D> visualObs,
         float reward,

UnitySDK/Assets/ML-Agents/Scripts/Academy.cs

              "docs/Learning-Environment-Design-Academy.md")]
     public abstract class Academy : MonoBehaviour
     {
+        [SerializeField] 
+        public BroadcastHub broadcastHub = new BroadcastHub();
+        
         private const string kApiVersion = "API-5";
 
         // Fields provided in the Inspector
         /// </summary>
         private void InitializeEnvironment()
         {
-            // Retrieve Brain and initialize Academy
-            var brains = GetBrains(gameObject);
-            MLAgents.Communicator communicator = null;
+            Communicator communicator = null;
+            var exposedBrains = broadcastHub.broadcastingBrains.Where(x => x != null).ToList();;
+            var controlledBrains = broadcastHub.broadcastingBrains.Where(
+                x => x != null && x is LearningBrain && broadcastHub.IsControlled(x));
+            foreach (LearningBrain brain in controlledBrains)
+            {
+                brain.SetToControlledExternally();
+            }
+            
-                communicator = new MLAgents.RPCCommunicator(
-                    new MLAgents.CommunicatorParameters
+                communicator = new RPCCommunicator(
+                    new CommunicatorParameters
                     {
                         port = ReadArgs()
                     });
             catch
             {
                 communicator = null;
-                var externalBrain = brains.FirstOrDefault(b => b.brainType == BrainType.External);
-                if (externalBrain != null)
+                if (controlledBrains.ToList().Count > 0)
-                    communicator = new MLAgents.RPCCommunicator(
-                        new MLAgents.CommunicatorParameters
+                    communicator = new RPCCommunicator(
+                        new CommunicatorParameters
                         {
                             port = 5005
                         });
             brainBatcher = new Batcher(communicator);
 
-            // Initialize Brains and communicator (if present)
-            foreach (var brain in brains)
+            foreach (var trainingBrain in exposedBrains)
-                brain.InitializeBrain(this, brainBatcher);
+                trainingBrain.SetBatcher(brainBatcher);
             }
 
             if (communicator != null)
                     new CommunicatorObjects.UnityRLInitializationOutput();
                 academyParameters.Name = gameObject.name;
                 academyParameters.Version = kApiVersion;
-                foreach (var brain in brains)
+                foreach (var brain in exposedBrains)
-                        bp.ToProto(
-                            brain.gameObject.name,
-                            (CommunicatorObjects.BrainTypeProto)
-                            brain.brainType));
+                        bp.ToProto(brain.name, broadcastHub.IsControlled(brain)));
-                
-
-                    new MLAgents.CommunicatorObjects.EnvironmentParametersProto();
+                    new CommunicatorObjects.EnvironmentParametersProto();
                 foreach (var key in resetParameters.Keys)
                 {
                     academyParameters.EnvironmentParameters.FloatParameters.Add(
             {
                 lastCommunicatorMessageNumber = brainBatcher.GetNumberMessageReceived();
                 if (brainBatcher.GetCommand() ==
-                    MLAgents.CommunicatorObjects.CommandProto.Reset)
+                    CommunicatorObjects.CommandProto.Reset)
                 {
                     UpdateResetParameters();
 
                 }
 
                 if (brainBatcher.GetCommand() ==
-                    MLAgents.CommunicatorObjects.CommandProto.Quit)
+                    CommunicatorObjects.CommandProto.Quit)
                 {
 #if UNITY_EDITOR
                     EditorApplication.isPlaying = false;
         void FixedUpdate()
         {
             EnvironmentStep();
-        }
-
-        /// <summary>
-        /// Helper method that retrieves the Brain objects that are currently
-        /// specified as children of the Academy within the Editor.
-        /// </summary>
-        /// <param name="academy">Academy.</param>
-        /// <returns>
-        /// List of brains currently attached to academy.
-        /// </returns>
-        static List<Brain> GetBrains(GameObject academy)
-        {
-            List<Brain> brains = new List<Brain>();
-            var transform = academy.transform;
-
-            for (var i = 0; i < transform.childCount; i++)
-            {
-                var child = transform.GetChild(i);
-                var brain = child.GetComponent<Brain>();
-
-                if (brain != null && child.gameObject.activeSelf)
-                {
-                    brains.Add(brain);
-                }
-            }
-
-            return brains;
         }
     }
 }

UnitySDK/Assets/ML-Agents/Scripts/ActionMasker.cs

             // indices for each branch.
             if (_startingActionIndices == null)
             {
-                _startingActionIndices = CreateActionStartinIndices();
+                _startingActionIndices = Utilities.CumSum(_brainParameters.vectorActionSize);
             }
             
             // Perform the masking
             {
                 Array.Clear(_currentMask, 0, _currentMask.Length);
             }
-        }
-
-        /// <summary>
-        /// Generates an array containing the starting indicies of each branch in the vector action
-        /// Makes a cumulative sum.
-        /// </summary>
-        /// <returns></returns>
-        private int[] CreateActionStartinIndices()
-        {
-            var vectorActionSize = _brainParameters.vectorActionSize;
-            var runningSum = 0;
-            var result = new int[vectorActionSize.Length + 1];
-            for (var actionIndex = 0;
-                actionIndex < vectorActionSize.Length; actionIndex++)
-            {
-                runningSum += vectorActionSize[actionIndex];
-                result[actionIndex + 1] = runningSum;
-            }
-            return result;
         }
 
         /// <summary>

UnitySDK/Assets/ML-Agents/Scripts/Agent.cs

                     "Vector Observation size mismatch between continuous " +
                     "agent {0} and brain {1}. " +
                     "Was Expecting {2} but received {3}. ",
-                    gameObject.name, brain.gameObject.name,
+                    gameObject.name, brain.name,
                     brain.brainParameters.vectorObservationSize,
                     info.vectorObservation.Count));
             }
                 throw new UnityAgentsException(string.Format(
                     "Not enough cameras for agent {0} : Bain {1} expecting at " +
                     "least {2} cameras but only {3} were present.",
-                    gameObject.name, brain.gameObject.name,
+                    gameObject.name, brain.name,
                     brain.brainParameters.cameraResolutions.Length,
                     agentParameters.agentCameras.Count));
             }

UnitySDK/Assets/ML-Agents/Scripts/Batcher.cs

         /// Is used by the academy to send the AcademyParameters to the communicator.
         /// </summary>
         /// <returns>The External Initialization Parameters received.</returns>
-        /// <param name="academyParameters">The Unity Initialization Paramters to be sent.</param>
+        /// <param name="academyParameters">The Unity Initialization Parameters to be sent.</param>
         public CommunicatorObjects.UnityRLInitializationInput SendAcademyParameters(
             CommunicatorObjects.UnityRLInitializationOutput academyParameters)
         {

UnitySDK/Assets/ML-Agents/Scripts/Brain.cs

-using System.Collections;
-using System.Collections.Generic;
+using System.Collections.Generic;
-using UnityEngine.UI;
-
-using System.Linq;
-
-
-// Class contains all necessary environment parameters
-// to be defined and sent to external agent
-
-    public enum BrainType
-    {
-        Player,
-        Heuristic,
-        External,
-        Internal
-    }
-
-    public enum SpaceType
+    /// <summary>
+    /// Brain receive data from Agents through calls to SendState. The brain then updates the
+    /// actions of the agents at each FixedUpdate.
+    /// The Brain encapsulates the decision making process. Every Agent must be assigned a Brain,
+    /// but you can use the same Brain with more than one Agent. You can also create several
+    /// Brains, attach each of the Brain to one or more than one Agent.
+    /// Brain assets has several important properties that you can set using the Inspector window.
+    /// These properties must be appropriate for the Agents using the Brain. For example, the
+    /// Vector Observation Space Size property must match the length of the feature
+    /// vector created by an Agent exactly.
+    /// </summary>
+    public abstract class Brain : ScriptableObject
-        discrete,
-        continuous
-    };
+        [SerializeField] public BrainParameters brainParameters;
+        protected Dictionary<Agent, AgentInfo> agentInfos =
+            new Dictionary<Agent, AgentInfo>(1024);
-
+        protected Batcher brainBatcher;
-/** Only need to be modified in the brain's inpector.
- * Defines what is the resolution of the camera
-*/
-    [System.Serializable]
-    public struct resolution
-    {
-        public int width;
-
-        /**< \brief The width of the observation in pixels */
-        public int height;
-
-        /**< \brief The height of the observation in pixels */
-        public bool blackAndWhite;
-        /**< \brief If true, the image will be in black and white. 
-         * If false, it will be in colors RGB */
-    }
-
-/** Should be modified via the Editor Inspector.
- * Defines brain-specific parameters
-*/
-    [System.Serializable]
-    public class BrainParameters
-    {
-        public int vectorObservationSize = 1;
-        /**< \brief If continuous : The length of the float vector that represents 
-         * the state
-         * <br> If discrete : The number of possible values the state can take*/
-
-        [Range(1, 50)] public int numStackedVectorObservations = 1;
-
-        public int[] vectorActionSize = new int[1]{1};
-        /**< \brief If continuous : The length of the float vector that represents
-         * the action
-         * <br> If discrete : The number of possible values the action can take*/
-
-        public resolution[] cameraResolutions;
-        /**<\brief  The list of observation resolutions for the brain */
-
-        public string[] vectorActionDescriptions;
-        /**< \brief The list of strings describing what the actions correpond to */
+        [System.NonSerialized]
+        private bool _isInitialized;
-        public SpaceType vectorActionSpaceType = SpaceType.discrete;
-        /**< \brief Defines if the action is discrete or continuous */
-        
-        /// Converts a Brain into to a Protobuff BrainInfoProto so it can be sent
+        /// Sets the Batcher of the Brain. The brain will call the batcher at every step and give
+        /// it the agent's data using SendBrainInfo at each DecideAction call.
-        /// <returns>The BrainInfoProto generated.</returns>
-        /// <param name="name">The name of the brain.</param>
-        /// <param name="type">The type of brain.</param>
-        public CommunicatorObjects.BrainParametersProto 
-            ToProto(string name, CommunicatorObjects.BrainTypeProto type)
+        /// <param name="batcher"> The Batcher the brain will use for the current session</param>
+        public void SetBatcher(Batcher batcher)
-            var brainParametersProto = new CommunicatorObjects.BrainParametersProto
-            {
-                VectorObservationSize = vectorObservationSize,
-                NumStackedVectorObservations = numStackedVectorObservations,
-                VectorActionSize = {vectorActionSize},
-                VectorActionSpaceType =
-                    (CommunicatorObjects.SpaceTypeProto)vectorActionSpaceType,
-                BrainName = name,
-                BrainType = type
-            };
-            brainParametersProto.VectorActionDescriptions.AddRange(vectorActionDescriptions);
-            foreach (resolution res in cameraResolutions)
+            if (batcher == null)
-                brainParametersProto.CameraResolutions.Add(
-                    new CommunicatorObjects.ResolutionProto
-                    {
-