Merge branch 'master' into asymm-envs

.yamato/python-ll-api-test.yml

   commands:
     - pip install pyyaml
     - python -u -m ml-agents.tests.yamato.setup_venv
-    - ./venv/bin/python ml-agents/tests/yamato/scripts/run_llapi.py
+    - ./venv/bin/python ml-agents/tests/yamato/scripts/run_llapi.py 
+    - ./venv/bin/python ml-agents/tests/yamato/scripts/run_llapi.py --env=artifacts/testPlayer-Basic
+    - ./venv/bin/python ml-agents/tests/yamato/scripts/run_llapi.py --env=artifacts/testPlayer-WallJump
+    - ./venv/bin/python ml-agents/tests/yamato/scripts/run_llapi.py --env=artifacts/testPlayer-Bouncer
   dependencies:
     - .yamato/standalone-build-test.yml#test_mac_standalone_{{ editor.version }}
   triggers:

.yamato/standalone-build-test.yml

     - pip install pyyaml
     - python -u -m ml-agents.tests.yamato.standalone_build_tests
     - python -u -m ml-agents.tests.yamato.standalone_build_tests --scene=Assets/ML-Agents/Examples/Basic/Scenes/Basic.unity
+    - python -u -m ml-agents.tests.yamato.standalone_build_tests --scene=Assets/ML-Agents/Examples/Bouncer/Scenes/Bouncer.unity 
+    - python -u -m ml-agents.tests.yamato.standalone_build_tests --scene=Assets/ML-Agents/Examples/WallJump/Scenes/WallJump.unity 
   triggers:
     cancel_old_ci: true
     changes:

Project/Assets/ML-Agents/Examples/3DBall/Demos/Expert3DBall.demo.meta

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Project/Assets/ML-Agents/Examples/3DBall/Prefabs/3DBallHardNew.prefab

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Project/Assets/ML-Agents/Examples/3DBall/Scripts/Ball3DAgent.cs

         SetResetParameters();
     }
 
-    public override float[] Heuristic()
+    public override void Heuristic(float[] actionsOut)
-        var action = new float[2];
-
-        action[0] = -Input.GetAxis("Horizontal");
-        action[1] = Input.GetAxis("Vertical");
-        return action;
+        actionsOut[0] = -Input.GetAxis("Horizontal");
+        actionsOut[1] = Input.GetAxis("Vertical");
     }
 
     public void SetBall()

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Project/Assets/ML-Agents/Examples/Bouncer/Scripts/BouncerAgent.cs

         }
     }
 
-    public override float[] Heuristic()
+    public override void Heuristic(float[] actionsOut)
-        var action = new float[3];
-
-        action[0] = Input.GetAxis("Horizontal");
-        action[1] = Input.GetKey(KeyCode.Space) ? 1.0f : 0.0f;
-        action[2] = Input.GetAxis("Vertical");
-        return action;
+        actionsOut[0] = Input.GetAxis("Horizontal");
+        actionsOut[1] = Input.GetKey(KeyCode.Space) ? 1.0f : 0.0f;
+        actionsOut[2] = Input.GetAxis("Vertical");
     }
 
     void Update()

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Project/Assets/ML-Agents/Examples/FoodCollector/Scripts/FoodCollectorAgent.cs

         MoveAgent(vectorAction);
     }
 
-    public override float[] Heuristic()
+    public override void Heuristic(float[] actionsOut)
-        var action = new float[4];
-            action[2] = 2f;
+            actionsOut[2] = 2f;
-            action[0] = 1f;
+            actionsOut[0] = 1f;
-            action[2] = 1f;
+            actionsOut[2] = 1f;
-            action[0] = 2f;
+            actionsOut[0] = 2f;
-        action[3] = Input.GetKey(KeyCode.Space) ? 1.0f : 0.0f;
-        return action;
+        actionsOut[3] = Input.GetKey(KeyCode.Space) ? 1.0f : 0.0f;
     }
 
     public override void OnEpisodeBegin()

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Project/Assets/ML-Agents/Examples/GridWorld/Scripts/GridAgent.cs

         }
     }
 
-    public override float[] Heuristic()
+    public override void Heuristic(float[] actionsOut)
+        actionsOut[0] = k_NoAction;
-            return new float[] { k_Right };
+            actionsOut[0] = k_Right;
-            return new float[] { k_Up };
+            actionsOut[0] = k_Up;
-            return new float[] { k_Left };
+            actionsOut[0] = k_Left;
-            return new float[] { k_Down };
+            actionsOut[0] = k_Down;
-        return new float[] { k_NoAction };
     }
 
     // to be implemented by the developer

Project/Assets/ML-Agents/Examples/Hallway/Demos/ExpertHallway.demo.meta

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Project/Assets/ML-Agents/Examples/Hallway/Prefabs/SymbolFinderArea.prefab

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Project/Assets/ML-Agents/Examples/Hallway/Scripts/HallwayAgent.cs

         }
     }
 
-    public override float[] Heuristic()
+    public override void Heuristic(float[] actionsOut)
+        actionsOut[0] = 0;
-            return new float[] { 3 };
+            actionsOut[0] = 3;
-        if (Input.GetKey(KeyCode.W))
+        else if (Input.GetKey(KeyCode.W))
-            return new float[] { 1 };
+            actionsOut[0] = 1;
-        if (Input.GetKey(KeyCode.A))
+        else if (Input.GetKey(KeyCode.A))
-            return new float[] { 4 };
+            actionsOut[0] = 4;
-        if (Input.GetKey(KeyCode.S))
+        else if (Input.GetKey(KeyCode.S))
-            return new float[] { 2 };
+            actionsOut[0] = 2;
-        return new float[] { 0 };
     }
 
     public override void OnEpisodeBegin()

Project/Assets/ML-Agents/Examples/PushBlock/Demos/ExpertPush.demo.meta

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+  m_ObservationStacks: 3
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+  m_ObservationStacks: 3
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Project/Assets/ML-Agents/Examples/PushBlock/Scripts/PushAgentBasic.cs

         AddReward(-1f / maxStep);
     }
 
-    public override float[] Heuristic()
+    public override void Heuristic(float[] actionsOut)
+        actionsOut[0] = 0;
-            return new float[] { 3 };
+            actionsOut[0] = 3;
-        if (Input.GetKey(KeyCode.W))
+        else if (Input.GetKey(KeyCode.W))
-            return new float[] { 1 };
+            actionsOut[0] = 1;
-        if (Input.GetKey(KeyCode.A))
+        else if (Input.GetKey(KeyCode.A))
-            return new float[] { 4 };
+            actionsOut[0] = 4;
-        if (Input.GetKey(KeyCode.S))
+        else if (Input.GetKey(KeyCode.S))
-            return new float[] { 2 };
+            actionsOut[0] = 2;
-        return new float[] { 0 };
     }
 
     /// <summary>

Project/Assets/ML-Agents/Examples/Pyramids/Demos/ExpertPyramid.demo.meta

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Project/Assets/ML-Agents/Examples/Pyramids/Prefabs/AreaPB.prefab

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Project/Assets/ML-Agents/Examples/Pyramids/Scripts/PyramidAgent.cs

         MoveAgent(vectorAction);
     }
 
-    public override float[] Heuristic()
+    public override void Heuristic(float[] actionsOut)
+        actionsOut[0] = 0;
-            return new float[] { 3 };
+            actionsOut[0] = 3;
-        if (Input.GetKey(KeyCode.W))
+        else if (Input.GetKey(KeyCode.W))
-            return new float[] { 1 };
+            actionsOut[0] = 1;
-        if (Input.GetKey(KeyCode.A))
+        else if (Input.GetKey(KeyCode.A))
-            return new float[] { 4 };
+            actionsOut[0] = 4;
-        if (Input.GetKey(KeyCode.S))
+        else if (Input.GetKey(KeyCode.S))
-            return new float[] { 2 };
+            actionsOut[0] = 2;
-        return new float[] { 0 };
     }
 
     public override void OnEpisodeBegin()

Project/Assets/ML-Agents/Examples/Reacher/Demos/ExpertReacher.demo.meta

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Project/Assets/ML-Agents/Examples/Reacher/Prefabs/Agent.prefab

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Project/Assets/ML-Agents/Examples/SharedAssets/Scripts/ModelOverrider.cs

         {
             if (m_MaxEpisodes > 0)
             {
-                if (m_NumSteps > m_MaxEpisodes * m_Agent.maxStep)
+                // For Agents without maxSteps, exit as soon as we've hit the target number of episodes.
+                // For Agents that specify maxStep, also make sure we've gone at least that many steps.
+                // Since we exit as soon as *any* Agent hits its target, the maxSteps condition keeps us running
+                // a bit longer in case there's an early failure.
+                if (m_Agent.CompletedEpisodes >= m_MaxEpisodes && m_NumSteps > m_MaxEpisodes * m_Agent.maxStep)
                 {
                     Application.Quit(0);
                 }

Project/Assets/ML-Agents/Examples/SharedAssets/Scripts/ProjectSettingsOverrides.cs

             Physics.defaultSolverIterations = solverIterations;
             Physics.defaultSolverVelocityIterations = solverVelocityIterations;
 
+            // Make sure the Academy singleton is initialized first, since it will create the SideChannels.
+            var academy = Academy.Instance;
             SideChannelUtils.GetSideChannel<FloatPropertiesChannel>().RegisterCallback("gravity", f => { Physics.gravity = new Vector3(0, -f, 0); });
         }
 
             Physics.defaultSolverVelocityIterations = m_OriginalSolverVelocityIterations;
         }
     }
-}
+}

Project/Assets/ML-Agents/Examples/Soccer/Prefabs/StrikersVsGoalieField.prefab

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Project/Assets/ML-Agents/Examples/Soccer/Scripts/AgentSoccer.cs

     float m_KickPower;
     int m_PlayerIndex;
     public SoccerFieldArea area;
+    // The coefficient for the reward for colliding with a ball. Set using curriculum.
-    float m_Power;
+    const float k_Power = 2000f;
+    float m_Existential;
     float m_LateralSpeed;
     float m_ForwardSpeed;
 
 
     public override void Initialize()
     {
+        m_Existential = 1f / maxStep;
         m_BehaviorParameters = gameObject.GetComponent<BehaviorParameters>();
         if (m_BehaviorParameters.TeamId == (int)Team.Blue)
         {
             team = Team.Purple;
             m_Transform = new Vector3(transform.position.x + 4f, .5f, transform.position.z);
         }
-        m_Power = 2000f;
         if (position == Position.Goalie)
         {
             m_LateralSpeed = 1.0f;
         if (position == Position.Goalie)
         {
             // Existential bonus for Goalies.
-            AddReward(1f / 3000f);
+            AddReward(m_Existential);
-            AddReward(-1f / 3000f);
+            AddReward(-m_Existential);
-            timePenalty += -1f / 3000f;
+            timePenalty -= m_Existential;
-    public override float[] Heuristic()
+    public override void Heuristic(float[] actionsOut)
-        var action = new float[3];
-            action[0] = 1f;
+            actionsOut[0] = 1f;
-            action[0] = 2f;
+            actionsOut[0] = 2f;
-            action[2] = 1f;
+            actionsOut[2] = 1f;
-            action[2] = 2f;
+            actionsOut[2] = 2f;
-            action[1] = 1f;
+            actionsOut[1] = 1f;
-            action[1] = 2f;
+            actionsOut[1] = 2f;
-        return action;
     }
     /// <summary>
     /// Used to provide a "kick" to the ball.
-        var force = m_Power * m_KickPower;
+        var force = k_Power * m_KickPower;
-            force = m_Power;
+            force = k_Power;
-            // Generic gets curriculum
-            if (position == Position.Generic)
-            {
-                AddReward(.2f * m_BallTouch);
-            }
+            AddReward(.2f * m_BallTouch);
             var dir = c.contacts[0].point - transform.position;
             dir = dir.normalized;
             c.gameObject.GetComponent<Rigidbody>().AddForce(dir * force);

Project/Assets/ML-Agents/Examples/Tennis/Demos/ExpertTennis.demo.meta

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     11400000: Assets/ML-Agents/Examples/Tennis/Demos/ExpertTennis.demo
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Project/Assets/ML-Agents/Examples/Tennis/Scripts/TennisAgent.cs

         m_TextComponent.text = score.ToString();
     }
 
-    public override float[] Heuristic()
+    public override void Heuristic(float[] actionsOut)
-        var action = new float[3];
-
-        action[0] = Input.GetAxis("Horizontal");    // Racket Movement
-        action[1] = Input.GetKey(KeyCode.Space) ? 1f : 0f;   // Racket Jumping
-        action[2] = Input.GetAxis("Vertical");   // Racket Rotation  
-        return action;
+        actionsOut[0] = Input.GetAxis("Horizontal");    // Racket Movement
+        actionsOut[1] = Input.GetKey(KeyCode.Space) ? 1f : 0f;   // Racket Jumping
+        actionsOut[2] = Input.GetAxis("Vertical");   // Racket Rotation
     }
 
     void OnCollisionEnter(Collision c)

Project/Assets/ML-Agents/Examples/Walker/Demos/ExpertWalker.demo.meta

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   m_TagString: Untagged
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   m_BehaviorName: Walker
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+  m_UseChildSensors: 1
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