rays and disc

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

   m_Name: 
   m_EditorClassIdentifier: 
   m_BrainParameters:
-    VectorObservationSize: 3
+    VectorObservationSize: 10
-      m_NumContinuousActions: 3
-      BranchSizes: 030000000300000003000000
-    VectorActionSize: 
+      m_NumContinuousActions: 0
+      BranchSizes: 0300000003000000030000000a000000
+    VectorActionSize: 0300000003000000030000000a000000
     VectorActionDescriptions: []
     VectorActionSpaceType: 0
     hasUpgradedBrainParametersWithActionSpec: 1
   m_Name: 
   m_EditorClassIdentifier: 
   m_BrainParameters:
-    VectorObservationSize: 3
+    VectorObservationSize: 10
-      m_NumContinuousActions: 3
-      BranchSizes: 030000000300000003000000
-    VectorActionSize: 
+      m_NumContinuousActions: 0
+      BranchSizes: 0300000003000000030000000a000000
+    VectorActionSize: 0300000003000000030000000a000000
     VectorActionDescriptions: []
     VectorActionSpaceType: 0
     hasUpgradedBrainParametersWithActionSpec: 1
   m_Name: 
   m_EditorClassIdentifier: 
   m_BrainParameters:
-    VectorObservationSize: 3
+    VectorObservationSize: 10
-      m_NumContinuousActions: 3
-      BranchSizes: 030000000300000003000000
-    VectorActionSize: 
+      m_NumContinuousActions: 0
+      BranchSizes: 0300000003000000030000000a000000
+    VectorActionSize: 0300000003000000030000000a000000
     VectorActionDescriptions: []
     VectorActionSpaceType: 0
     hasUpgradedBrainParametersWithActionSpec: 1
   m_Name: 
   m_EditorClassIdentifier: 
   m_BrainParameters:
-    VectorObservationSize: 3
+    VectorObservationSize: 10
-      m_NumContinuousActions: 3
-      BranchSizes: 030000000300000003000000
-    VectorActionSize: 
+      m_NumContinuousActions: 0
+      BranchSizes: 0300000003000000030000000a000000
+    VectorActionSize: 0300000003000000030000000a000000
     VectorActionDescriptions: []
     VectorActionSpaceType: 0
     hasUpgradedBrainParametersWithActionSpec: 1

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

     public Team team;
     float m_KickPower;
     int m_PlayerIndex;
+    int m_Previous = 0;
     public SoccerFieldArea area;
 
     // The coefficient for the reward for colliding with a ball. Set using curriculum.
     float m_Existential;
     float m_LateralSpeed;
     float m_ForwardSpeed;
-    float[] m_Message = new float[3];
+    float[] m_Message = new float[10];
     public GameObject teammate_gb;
     AgentSoccer teammate;
 
             timePenalty -= m_Existential;
         }
         MoveAgent(actionBuffers.DiscreteActions);
-        teammate.tellAgent(actionBuffers.ContinuousActions.Array);
+        teammate.tellAgent(actionBuffers.DiscreteActions[3]);
+
-    public void tellAgent(float[] message)
+    public void tellAgent(int message)
-        m_Message = message;
+        m_Message[m_Previous] = 0f;
+        m_Message[message] = 1f;
+        m_Previous = message;
     }
 
     public override void Heuristic(in ActionBuffers actionsOut)

config/ppo/SoccerTwos.yaml

     network_settings:
       normalize: false
       hidden_units: 512
-      num_layers: 2
+      num_layers: 3
       vis_encode_type: simple
     reward_signals:
       extrinsic:
-    max_steps: 50000000
+    max_steps: 100000000
     time_horizon: 1000
     summary_freq: 10000
     threaded: false
       window: 10
       play_against_latest_model_ratio: 0.5
       initial_elo: 1200.0
+env_settings:
+  num_envs: 4