Merge branch 'develop-taggedobservations' into active-variablespeed

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

         {
             return SensorCompressionType.None;
         }
+
+        /// <inheritdoc/>
+        public virtual SensorType GetSensorType()
+        {
+            return SensorType.Observation;
+        }
     }
 }

com.unity.ml-agents/Runtime/Academy.cs

         }
 
         EnvironmentParameters m_EnvironmentParameters;
+        AgentParameters m_AgentParameters;
         StatsRecorder m_StatsRecorder;
 
         /// <summary>
         public EnvironmentParameters EnvironmentParameters
         {
             get { return m_EnvironmentParameters; }
+        }
+
+        public AgentParameters AgentParameters
+        {
+            get { return m_AgentParameters; }
         }
 
         /// <summary>
 
             SideChannelManager.RegisterSideChannel(new EngineConfigurationChannel());
             m_EnvironmentParameters = new EnvironmentParameters();
+            m_AgentParameters = new AgentParameters();
             m_StatsRecorder = new StatsRecorder();
 
             // Try to launch the communicator by using the arguments passed at launch

com.unity.ml-agents/Runtime/Agent.cs

                 Array.Copy(action, m_Action.vectorActions, action.Length);
             }
         }
+
+        public float GetParameterWithDefault(string key, float defaultValue)
+        {
+            return Academy.Instance.AgentParameters.GetWithDefault(m_EpisodeId, key, defaultValue);
+        }
     }
 }

com.unity.ml-agents/Runtime/Communicator/GrpcExtensions.cs

                     CompressionType = (CompressionTypeProto)obs.CompressionType,
                 };
             }
-
             obsProto.Shape.AddRange(obs.Shape);
             return obsProto;
         }
                     CompressionType = (CompressionTypeProto)sensor.GetCompressionType(),
                 };
             }
+            observationProto.SensorType = (SensorTypeProto)sensor.GetSensorType();
             observationProto.Shape.AddRange(shape);
             return observationProto;
         }

com.unity.ml-agents/Runtime/Grpc/CommunicatorObjects/Observation.cs

       byte[] descriptorData = global::System.Convert.FromBase64String(
           string.Concat(
             "CjRtbGFnZW50c19lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL29ic2VydmF0",
-            "aW9uLnByb3RvEhRjb21tdW5pY2F0b3Jfb2JqZWN0cyL5AQoQT2JzZXJ2YXRp",
+            "aW9uLnByb3RvEhRjb21tdW5pY2F0b3Jfb2JqZWN0cyK1AgoQT2JzZXJ2YXRp",
-            "RmxvYXREYXRhSAAaGQoJRmxvYXREYXRhEgwKBGRhdGEYASADKAJCEgoQb2Jz",
-            "ZXJ2YXRpb25fZGF0YSopChRDb21wcmVzc2lvblR5cGVQcm90bxIICgROT05F",
-            "EAASBwoDUE5HEAFCJaoCIlVuaXR5Lk1MQWdlbnRzLkNvbW11bmljYXRvck9i",
-            "amVjdHNiBnByb3RvMw=="));
+            "RmxvYXREYXRhSAASOgoLc2Vuc29yX3R5cGUYBSABKA4yJS5jb21tdW5pY2F0",
+            "b3Jfb2JqZWN0cy5TZW5zb3JUeXBlUHJvdG8aGQoJRmxvYXREYXRhEgwKBGRh",
+            "dGEYASADKAJCEgoQb2JzZXJ2YXRpb25fZGF0YSopChRDb21wcmVzc2lvblR5",
+            "cGVQcm90bxIICgROT05FEAASBwoDUE5HEAEqRAoPU2Vuc29yVHlwZVByb3Rv",
+            "Eg8KC09CU0VSVkFUSU9OEAASFAoQUEFSQU1FVEVSSVpBVElPThABEgoKBlJF",
+            "V0FSRBACQiWqAiJVbml0eS5NTEFnZW50cy5Db21tdW5pY2F0b3JPYmplY3Rz",
+            "YgZwcm90bzM="));
-          new pbr::GeneratedClrTypeInfo(new[] {typeof(global::Unity.MLAgents.CommunicatorObjects.CompressionTypeProto), }, new pbr::GeneratedClrTypeInfo[] {
-            new pbr::GeneratedClrTypeInfo(typeof(global::Unity.MLAgents.CommunicatorObjects.ObservationProto), global::Unity.MLAgents.CommunicatorObjects.ObservationProto.Parser, new[]{ "Shape", "CompressionType", "CompressedData", "FloatData" }, new[]{ "ObservationData" }, null, new pbr::GeneratedClrTypeInfo[] { new pbr::GeneratedClrTypeInfo(typeof(global::Unity.MLAgents.CommunicatorObjects.ObservationProto.Types.FloatData), global::Unity.MLAgents.CommunicatorObjects.ObservationProto.Types.FloatData.Parser, new[]{ "Data" }, null, null, null)})
+          new pbr::GeneratedClrTypeInfo(new[] {typeof(global::Unity.MLAgents.CommunicatorObjects.CompressionTypeProto), typeof(global::Unity.MLAgents.CommunicatorObjects.SensorTypeProto), }, new pbr::GeneratedClrTypeInfo[] {
+            new pbr::GeneratedClrTypeInfo(typeof(global::Unity.MLAgents.CommunicatorObjects.ObservationProto), global::Unity.MLAgents.CommunicatorObjects.ObservationProto.Parser, new[]{ "Shape", "CompressionType", "CompressedData", "FloatData", "SensorType" }, new[]{ "ObservationData" }, null, new pbr::GeneratedClrTypeInfo[] { new pbr::GeneratedClrTypeInfo(typeof(global::Unity.MLAgents.CommunicatorObjects.ObservationProto.Types.FloatData), global::Unity.MLAgents.CommunicatorObjects.ObservationProto.Types.FloatData.Parser, new[]{ "Data" }, null, null, null)})
           }));
     }
     #endregion
   internal enum CompressionTypeProto {
     [pbr::OriginalName("NONE")] None = 0,
     [pbr::OriginalName("PNG")] Png = 1,
+  }
+
+  internal enum SensorTypeProto {
+    [pbr::OriginalName("OBSERVATION")] Observation = 0,
+    [pbr::OriginalName("PARAMETERIZATION")] Parameterization = 1,
+    [pbr::OriginalName("REWARD")] Reward = 2,
   }
 
   #endregion
     public ObservationProto(ObservationProto other) : this() {
       shape_ = other.shape_.Clone();
       compressionType_ = other.compressionType_;
+      sensorType_ = other.sensorType_;
       switch (other.ObservationDataCase) {
         case ObservationDataOneofCase.CompressedData:
           CompressedData = other.CompressedData;
       }
     }
 
+    /// <summary>Field number for the "sensor_type" field.</summary>
+    public const int SensorTypeFieldNumber = 5;
+    private global::Unity.MLAgents.CommunicatorObjects.SensorTypeProto sensorType_ = 0;
+    [global::System.Diagnostics.DebuggerNonUserCodeAttribute]
+    public global::Unity.MLAgents.CommunicatorObjects.SensorTypeProto SensorType {
+      get { return sensorType_; }
+      set {
+        sensorType_ = value;
+      }
+    }
+
     private object observationData_;
     /// <summary>Enum of possible cases for the "observation_data" oneof.</summary>
     public enum ObservationDataOneofCase {
       if (CompressionType != other.CompressionType) return false;
       if (CompressedData != other.CompressedData) return false;
       if (!object.Equals(FloatData, other.FloatData)) return false;
+      if (SensorType != other.SensorType) return false;
       if (ObservationDataCase != other.ObservationDataCase) return false;
       return Equals(_unknownFields, other._unknownFields);
     }
       if (CompressionType != 0) hash ^= CompressionType.GetHashCode();
       if (observationDataCase_ == ObservationDataOneofCase.CompressedData) hash ^= CompressedData.GetHashCode();
       if (observationDataCase_ == ObservationDataOneofCase.FloatData) hash ^= FloatData.GetHashCode();
+      if (SensorType != 0) hash ^= SensorType.GetHashCode();
       hash ^= (int) observationDataCase_;
       if (_unknownFields != null) {
         hash ^= _unknownFields.GetHashCode();
         output.WriteRawTag(34);
         output.WriteMessage(FloatData);
       }
+      if (SensorType != 0) {
+        output.WriteRawTag(40);
+        output.WriteEnum((int) SensorType);
+      }
       if (_unknownFields != null) {
         _unknownFields.WriteTo(output);
       }
       if (observationDataCase_ == ObservationDataOneofCase.FloatData) {
         size += 1 + pb::CodedOutputStream.ComputeMessageSize(FloatData);
       }
+      if (SensorType != 0) {
+        size += 1 + pb::CodedOutputStream.ComputeEnumSize((int) SensorType);
+      }
       if (_unknownFields != null) {
         size += _unknownFields.CalculateSize();
       }
       shape_.Add(other.shape_);
       if (other.CompressionType != 0) {
         CompressionType = other.CompressionType;
+      }
+      if (other.SensorType != 0) {
+        SensorType = other.SensorType;
       }
       switch (other.ObservationDataCase) {
         case ObservationDataOneofCase.CompressedData:
             }
             input.ReadMessage(subBuilder);
             FloatData = subBuilder;
+            break;
+          }
+          case 40: {
+            sensorType_ = (global::Unity.MLAgents.CommunicatorObjects.SensorTypeProto) input.ReadEnum();
             break;
           }
         }

com.unity.ml-agents/Runtime/Sensors/CameraSensor.cs

         }
 
         /// <summary>
+        /// Camera sensors are always Observations.
+        /// </summary>
+        /// <returns>Sensor type of observation.</returns>
+        public SensorType GetSensorType()
+        {
+            return SensorType.Observation;
+        }
+
+
+        /// <summary>
         /// Generates a compressed image. This can be valuable in speeding-up training.
         /// </summary>
         /// <returns>Compressed image.</returns>

com.unity.ml-agents/Runtime/Sensors/ISensor.cs

     }
 
     /// <summary>
+    /// The compression setting for visual/camera observations.
+    /// </summary>
+    public enum SensorType
+    {
+        /// <summary>
+        /// Sensor represents an agent's observation.
+        /// </summary>
+        Observation,
+
+        /// <summary>
+        /// Sensor represents an agent's task/goal parameterization.
+        /// </summary>
+        Parameterization,
+
+        /// <summary>
+        /// Sensor represents one or more reward signals.
+        /// </summary>
+        Reward
+    }
+
+    /// <summary>
     /// Sensor interface for generating observations.
     /// </summary>
     public interface ISensor
         /// </summary>
         /// <returns>The name of the sensor.</returns>
         string GetName();
+
+
+        /// <summary>
+        /// Get the semantic meaning of the sensor, i.e. whether it is an observation or other type
+        /// of data to be sent to the Agent.
+        /// </summary>
+        /// <returns>The type of the sensor.</returns>
+        SensorType GetSensorType();
     }
 
 

com.unity.ml-agents/Runtime/Sensors/RayPerceptionSensor.cs

             return SensorCompressionType.None;
         }
 
+        /// <inheritdoc/>
+        public SensorType GetSensorType()
+        {
+            return SensorType.Observation;
+        }
+
         /// <summary>
         /// Evaluates the raycasts to be used as part of an observation of an agent.
         /// </summary>

com.unity.ml-agents/Runtime/Sensors/Reflection/ReflectionSensorBase.cs

         }
 
         /// <inheritdoc/>
+        public SensorType GetSensorType()
+        {
+            return SensorType.Observation;
+        }
+
+        /// <inheritdoc/>
         public string GetName()
         {
             return m_SensorName;

com.unity.ml-agents/Runtime/Sensors/RenderTextureSensor.cs

         }
 
         /// <summary>
+        /// RenderTexture sensors are always Observations.
+        /// </summary>
+        /// <returns>Sensor type of observation.</returns>
+        public SensorType GetSensorType()
+        {
+            return SensorType.Observation;
+        }
+
+        /// <summary>
         /// Converts a RenderTexture to a 2D texture.
         /// </summary>
         /// <returns>The 2D texture.</returns>

com.unity.ml-agents/Runtime/Sensors/StackingSensor.cs

             return SensorCompressionType.None;
         }
 
+        /// <inheritdoc/>
+        public SensorType GetSensorType()
+        {
+            return SensorType.Observation;
+        }
+
         // TODO support stacked compressed observations (byte stream)
     }
 }

com.unity.ml-agents/Runtime/Sensors/VectorSensor.cs

             return SensorCompressionType.None;
         }
 
+        /// <inheritdoc/>
+        public virtual SensorType GetSensorType()
+        {
+            return SensorType.Observation;
+        }
+
         void Clear()
         {
             m_Observations.Clear();

com.unity.ml-agents/Tests/Editor/MLAgentsEditModeTest.cs

         {
             numResetCalls++;
         }
+
+        public SensorType GetSensorType()
+        {
+            return SensorType.Observation;
+        }
     }
 
     [TestFixture]

com.unity.ml-agents/Tests/Editor/ParameterLoaderTest.cs

             return SensorCompressionType.None;
         }
 
+        public SensorType GetSensorType()
+        {
+            return SensorType.Observation;
+        }
+
         public string GetName()
         {
             return m_Name;

com.unity.ml-agents/Tests/Editor/Sensor/FloatVisualSensorTests.cs

         {
             return SensorCompressionType.None;
         }
+
+        public SensorType GetSensorType()
+        {
+            return SensorType.Observation;
+        }
     }
 
     public class FloatVisualSensorTests

com.unity.ml-agents/Tests/Editor/Sensor/SensorShapeValidatorTests.cs

         {
             return SensorCompressionType.None;
         }
+
+        public SensorType GetSensorType()
+        {
+            return SensorType.Observation;
+        }
     }
 
     public class SensorShapeValidatorTests

ml-agents-envs/mlagents_envs/base_env.py

     CONTINUOUS = 1
 
 
+class SensorType(Enum):
+    OBSERVATION = 0
+    PARAMETERIZATION = 1
+    REWARD = 2
+
+
 class BehaviorSpec(NamedTuple):
     """
     A NamedTuple to containing information about the observations and actions
     """
 
     observation_shapes: List[Tuple]
+    sensor_types: List[SensorType]
     action_type: ActionType
     action_shape: Union[int, Tuple[int, ...]]
 

ml-agents-envs/mlagents_envs/communicator_objects/observation_pb2.py

   name='mlagents_envs/communicator_objects/observation.proto',
   package='communicator_objects',
   syntax='proto3',
-  serialized_pb=_b('\n4mlagents_envs/communicator_objects/observation.proto\x12\x14\x63ommunicator_objects\"\xf9\x01\n\x10ObservationProto\x12\r\n\x05shape\x18\x01 \x03(\x05\x12\x44\n\x10\x63ompression_type\x18\x02 \x01(\x0e\x32*.communicator_objects.CompressionTypeProto\x12\x19\n\x0f\x63ompressed_data\x18\x03 \x01(\x0cH\x00\x12\x46\n\nfloat_data\x18\x04 \x01(\x0b\x32\x30.communicator_objects.ObservationProto.FloatDataH\x00\x1a\x19\n\tFloatData\x12\x0c\n\x04\x64\x61ta\x18\x01 \x03(\x02\x42\x12\n\x10observation_data*)\n\x14\x43ompressionTypeProto\x12\x08\n\x04NONE\x10\x00\x12\x07\n\x03PNG\x10\x01\x42%\xaa\x02\"Unity.MLAgents.CommunicatorObjectsb\x06proto3')
+  serialized_pb=_b('\n4mlagents_envs/communicator_objects/observation.proto\x12\x14\x63ommunicator_objects\"\xb5\x02\n\x10ObservationProto\x12\r\n\x05shape\x18\x01 \x03(\x05\x12\x44\n\x10\x63ompression_type\x18\x02 \x01(\x0e\x32*.communicator_objects.CompressionTypeProto\x12\x19\n\x0f\x63ompressed_data\x18\x03 \x01(\x0cH\x00\x12\x46\n\nfloat_data\x18\x04 \x01(\x0b\x32\x30.communicator_objects.ObservationProto.FloatDataH\x00\x12:\n\x0bsensor_type\x18\x05 \x01(\x0e\x32%.communicator_objects.SensorTypeProto\x1a\x19\n\tFloatData\x12\x0c\n\x04\x64\x61ta\x18\x01 \x03(\x02\x42\x12\n\x10observation_data*)\n\x14\x43ompressionTypeProto\x12\x08\n\x04NONE\x10\x00\x12\x07\n\x03PNG\x10\x01*D\n\x0fSensorTypeProto\x12\x0f\n\x0bOBSERVATION\x10\x00\x12\x14\n\x10PARAMETERIZATION\x10\x01\x12\n\n\x06REWARD\x10\x02\x42%\xaa\x02\"Unity.MLAgents.CommunicatorObjectsb\x06proto3')
 )
 
 _COMPRESSIONTYPEPROTO = _descriptor.EnumDescriptor(
   ],
   containing_type=None,
   options=None,
-  serialized_start=330,
-  serialized_end=371,
+  serialized_start=390,
+  serialized_end=431,
+_SENSORTYPEPROTO = _descriptor.EnumDescriptor(
+  name='SensorTypeProto',
+  full_name='communicator_objects.SensorTypeProto',
+  filename=None,
+  file=DESCRIPTOR,
+  values=[
+    _descriptor.EnumValueDescriptor(
+      name='OBSERVATION', index=0, number=0,
+      options=None,
+      type=None),
+    _descriptor.EnumValueDescriptor(
+      name='PARAMETERIZATION', index=1, number=1,
+      options=None,
+      type=None),
+    _descriptor.EnumValueDescriptor(
+      name='REWARD', index=2, number=2,
+      options=None,
+      type=None),
+  ],
+  containing_type=None,
+  options=None,
+  serialized_start=433,
+  serialized_end=501,
+)
+_sym_db.RegisterEnumDescriptor(_SENSORTYPEPROTO)
+
+SensorTypeProto = enum_type_wrapper.EnumTypeWrapper(_SENSORTYPEPROTO)
+OBSERVATION = 0
+PARAMETERIZATION = 1
+REWARD = 2
 
 
 
   extension_ranges=[],
   oneofs=[
   ],
-  serialized_start=283,
-  serialized_end=308,
+  serialized_start=343,
+  serialized_end=368,
 )
 
 _OBSERVATIONPROTO = _descriptor.Descriptor(
       message_type=None, enum_type=None, containing_type=None,
       is_extension=False, extension_scope=None,
       options=None, file=DESCRIPTOR),
+    _descriptor.FieldDescriptor(
+      name='sensor_type', full_name='communicator_objects.ObservationProto.sensor_type', index=4,
+      number=5, type=14, cpp_type=8, label=1,
+      has_default_value=False, default_value=0,
+      message_type=None, enum_type=None, containing_type=None,
+      is_extension=False, extension_scope=None,
+      options=None, file=DESCRIPTOR),
   ],
   extensions=[
   ],
       index=0, containing_type=None, fields=[]),
   ],
   serialized_start=79,
-  serialized_end=328,
+  serialized_end=388,
+_OBSERVATIONPROTO.fields_by_name['sensor_type'].enum_type = _SENSORTYPEPROTO
 _OBSERVATIONPROTO.oneofs_by_name['observation_data'].fields.append(
   _OBSERVATIONPROTO.fields_by_name['compressed_data'])
 _OBSERVATIONPROTO.fields_by_name['compressed_data'].containing_oneof = _OBSERVATIONPROTO.oneofs_by_name['observation_data']
 DESCRIPTOR.message_types_by_name['ObservationProto'] = _OBSERVATIONPROTO
 DESCRIPTOR.enum_types_by_name['CompressionTypeProto'] = _COMPRESSIONTYPEPROTO
+DESCRIPTOR.enum_types_by_name['SensorTypeProto'] = _SENSORTYPEPROTO
 _sym_db.RegisterFileDescriptor(DESCRIPTOR)
 
 ObservationProto = _reflection.GeneratedProtocolMessageType('ObservationProto', (_message.Message,), dict(

ml-agents-envs/mlagents_envs/communicator_objects/observation_pb2.pyi

 from google.protobuf.descriptor import (
     Descriptor as google___protobuf___descriptor___Descriptor,
     EnumDescriptor as google___protobuf___descriptor___EnumDescriptor,
+    FileDescriptor as google___protobuf___descriptor___FileDescriptor,
 )
 
 from google.protobuf.internal.containers import (
+from google.protobuf.internal.enum_type_wrapper import (
+    _EnumTypeWrapper as google___protobuf___internal___enum_type_wrapper____EnumTypeWrapper,
+)
+
 from google.protobuf.message import (
     Message as google___protobuf___message___Message,
 )
-    List as typing___List,
+    NewType as typing___NewType,
-    Tuple as typing___Tuple,
     cast as typing___cast,
 )
 
 builtin___bytes = bytes
 builtin___float = float
 builtin___int = int
-builtin___str = str
-class CompressionTypeProto(builtin___int):
+DESCRIPTOR: google___protobuf___descriptor___FileDescriptor = ...
+
+CompressionTypeProtoValue = typing___NewType('CompressionTypeProtoValue', builtin___int)
+type___CompressionTypeProtoValue = CompressionTypeProtoValue
+CompressionTypeProto: _CompressionTypeProto
+class _CompressionTypeProto(google___protobuf___internal___enum_type_wrapper____EnumTypeWrapper[CompressionTypeProtoValue]):
-    @classmethod
-    def Name(cls, number: builtin___int) -> builtin___str: ...
-    @classmethod
-    def Value(cls, name: builtin___str) -> 'CompressionTypeProto': ...
-    @classmethod
-    def keys(cls) -> typing___List[builtin___str]: ...
-    @classmethod
-    def values(cls) -> typing___List['CompressionTypeProto']: ...
-    @classmethod
-    def items(cls) -> typing___List[typing___Tuple[builtin___str, 'CompressionTypeProto']]: ...
-    NONE = typing___cast('CompressionTypeProto', 0)
-    PNG = typing___cast('CompressionTypeProto', 1)
-NONE = typing___cast('CompressionTypeProto', 0)
-PNG = typing___cast('CompressionTypeProto', 1)
+    NONE = typing___cast(CompressionTypeProtoValue, 0)
+    PNG = typing___cast(CompressionTypeProtoValue, 1)
+NONE = typing___cast(CompressionTypeProtoValue, 0)
+PNG = typing___cast(CompressionTypeProtoValue, 1)
+type___CompressionTypeProto = CompressionTypeProto
+
+SensorTypeProtoValue = typing___NewType('SensorTypeProtoValue', builtin___int)
+type___SensorTypeProtoValue = SensorTypeProtoValue
+SensorTypeProto: _SensorTypeProto
+class _SensorTypeProto(google___protobuf___internal___enum_type_wrapper____EnumTypeWrapper[SensorTypeProtoValue]):
+    DESCRIPTOR: google___protobuf___descriptor___EnumDescriptor = ...
+    OBSERVATION = typing___cast(SensorTypeProtoValue, 0)
+    PARAMETERIZATION = typing___cast(SensorTypeProtoValue, 1)
+    REWARD = typing___cast(SensorTypeProtoValue, 2)
+OBSERVATION = typing___cast(SensorTypeProtoValue, 0)
+PARAMETERIZATION = typing___cast(SensorTypeProtoValue, 1)
+REWARD = typing___cast(SensorTypeProtoValue, 2)
+type___SensorTypeProto = SensorTypeProto
-        data = ... # type: google___protobuf___internal___containers___RepeatedScalarFieldContainer[builtin___float]
+        data: google___protobuf___internal___containers___RepeatedScalarFieldContainer[builtin___float] = ...
-        @classmethod
-        def FromString(cls, s: builtin___bytes) -> ObservationProto.FloatData: ...
-        def MergeFrom(self, other_msg: google___protobuf___message___Message) -> None: ...
-        def CopyFrom(self, other_msg: google___protobuf___message___Message) -> None: ...
-        if sys.version_info >= (3,):
-            def ClearField(self, field_name: typing_extensions___Literal[u"data"]) -> None: ...
-        else:
-            def ClearField(self, field_name: typing_extensions___Literal[u"data",b"data"]) -> None: ...
+        def ClearField(self, field_name: typing_extensions___Literal[u"data",b"data"]) -> None: ...
+    type___FloatData = FloatData
-    shape = ... # type: google___protobuf___internal___containers___RepeatedScalarFieldContainer[builtin___int]
-    compression_type = ... # type: CompressionTypeProto
-    compressed_data = ... # type: builtin___bytes
+    shape: google___protobuf___internal___containers___RepeatedScalarFieldContainer[builtin___int] = ...
+    compression_type: type___CompressionTypeProtoValue = ...
+    compressed_data: builtin___bytes = ...
+    sensor_type: type___SensorTypeProtoValue = ...
-    def float_data(self) -> ObservationProto.FloatData: ...
+    def float_data(self) -> type___ObservationProto.FloatData: ...
-        compression_type : typing___Optional[CompressionTypeProto] = None,
+        compression_type : typing___Optional[type___CompressionTypeProtoValue] = None,
-        float_data : typing___Optional[ObservationProto.FloatData] = None,
+        float_data : typing___Optional[type___ObservationProto.FloatData] = None,
+        sensor_type : typing___Optional[type___SensorTypeProtoValue] = None,
-    @classmethod
-    def FromString(cls, s: builtin___bytes) -> ObservationProto: ...
-    def MergeFrom(self, other_msg: google___protobuf___message___Message) -> None: ...
-    def CopyFrom(self, other_msg: google___protobuf___message___Message) -> None: ...
-    if sys.version_info >= (3,):
-        def HasField(self, field_name: typing_extensions___Literal[u"compressed_data",u"float_data",u"observation_data"]) -> builtin___bool: ...
-        def ClearField(self, field_name: typing_extensions___Literal[u"compressed_data",u"compression_type",u"float_data",u"observation_data",u"shape"]) -> None: ...
-    else:
-        def HasField(self, field_name: typing_extensions___Literal[u"compressed_data",b"compressed_data",u"float_data",b"float_data",u"observation_data",b"observation_data"]) -> builtin___bool: ...
-        def ClearField(self, field_name: typing_extensions___Literal[u"compressed_data",b"compressed_data",u"compression_type",b"compression_type",u"float_data",b"float_data",u"observation_data",b"observation_data",u"shape",b"shape"]) -> None: ...
+    def HasField(self, field_name: typing_extensions___Literal[u"compressed_data",b"compressed_data",u"float_data",b"float_data",u"observation_data",b"observation_data"]) -> builtin___bool: ...
+    def ClearField(self, field_name: typing_extensions___Literal[u"compressed_data",b"compressed_data",u"compression_type",b"compression_type",u"float_data",b"float_data",u"observation_data",b"observation_data",u"sensor_type",b"sensor_type",u"shape",b"shape"]) -> None: ...
+type___ObservationProto = ObservationProto

ml-agents-envs/mlagents_envs/rpc_utils.py

 from mlagents_envs.base_env import (
     BehaviorSpec,
     ActionType,
+    SensorType,
     DecisionSteps,
     TerminalSteps,
 )
     :return: BehaviorSpec object.
     """
     observation_shape = [tuple(obs.shape) for obs in agent_info.observations]
+    sensor_type = [SensorType(obs.sensor_type) for obs in agent_info.observations]
     action_type = (
         ActionType.DISCRETE
         if brain_param_proto.vector_action_space_type == 0
         ] = brain_param_proto.vector_action_size[0]
     else:
         action_shape = tuple(brain_param_proto.vector_action_size)
-    return BehaviorSpec(observation_shape, action_type, action_shape)
+    return BehaviorSpec(observation_shape, sensor_type, action_type, action_shape)
 
 
 @timed

protobuf-definitions/proto/mlagents_envs/communicator_objects/observation.proto

     PNG = 1;
 }
 
+enum SensorTypeProto {
+    OBSERVATION = 0;
+    PARAMETERIZATION = 1;
+    REWARD = 2;
+}
+
 message ObservationProto {
     message FloatData {
         repeated float data = 1;
         bytes compressed_data = 3;
         FloatData float_data = 4;
     }
+    SensorTypeProto sensor_type = 5;
 }

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

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

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Project/Assets/ML-Agents/Examples/3DBall/Scripts/Task3DAgent.cs

+using UnityEngine;
+using Unity.MLAgents;
+using Unity.MLAgents.Sensors;
+
+public class Task3DAgent : Agent
+{
+    [Header("Specific to Ball3D")]
+    public GameObject ball;
+    Rigidbody m_BallRb;
+    EnvironmentParameters m_ResetParams;
+
+    TaskSensorComponent m_TaskSensor;
+
+    public override void Initialize()
+    {
+        m_BallRb = ball.GetComponent<Rigidbody>();
+        m_ResetParams = Academy.Instance.EnvironmentParameters;
+        SetResetParameters();
+    }
+
+    public override void CollectObservations(VectorSensor sensor)
+    {
+        sensor.AddObservation(gameObject.transform.rotation.z);
+        sensor.AddObservation(gameObject.transform.rotation.x);
+        sensor.AddObservation(ball.transform.position - gameObject.transform.position);
+        sensor.AddObservation(m_BallRb.velocity);
+        // Example of setting task parameterization to ball x position
+        m_TaskSensor = this.GetComponent<TaskSensorComponent>();
+        m_TaskSensor.AddParameterizaton(ball.transform.position.x);
+    }
+
+    public override void OnActionReceived(float[] vectorAction)
+    {
+        var actionZ = 2f * Mathf.Clamp(vectorAction[0], -1f, 1f);
+        var actionX = 2f * Mathf.Clamp(vectorAction[1], -1f, 1f);
+
+        if ((gameObject.transform.rotation.z < 0.25f && actionZ > 0f) ||
+            (gameObject.transform.rotation.z > -0.25f && actionZ < 0f))
+        {
+            gameObject.transform.Rotate(new Vector3(0, 0, 1), actionZ);
+        }
+
+        if ((gameObject.transform.rotation.x < 0.25f && actionX > 0f) ||
+            (gameObject.transform.rotation.x > -0.25f && actionX < 0f))
+        {
+            gameObject.transform.Rotate(new Vector3(1, 0, 0), actionX);
+        }
+        if ((ball.transform.position.y - gameObject.transform.position.y) < -2f ||
+            Mathf.Abs(ball.transform.position.x - gameObject.transform.position.x) > 3f ||
+            Mathf.Abs(ball.transform.position.z - gameObject.transform.position.z) > 3f)
+        {
+            SetReward(-1f);
+            EndEpisode();
+        }
+        else
+        {
+            SetReward(0.1f);
+        }
+    }
+
+    public override void OnEpisodeBegin()
+    {
+        gameObject.transform.rotation = new Quaternion(0f, 0f, 0f, 0f);
+        gameObject.transform.Rotate(new Vector3(1, 0, 0), Random.Range(-10f, 10f));
+        gameObject.transform.Rotate(new Vector3(0, 0, 1), Random.Range(-10f, 10f));
+        m_BallRb.velocity = new Vector3(0f, 0f, 0f);
+        ball.transform.position = new Vector3(Random.Range(-1.5f, 1.5f), 4f, Random.Range(-1.5f, 1.5f))
+            + gameObject.transform.position;
+        //Reset the parameters when the Agent is reset.
+        SetResetParameters();
+    }
+
+    public override void Heuristic(float[] actionsOut)
+    {
+        actionsOut[0] = -Input.GetAxis("Horizontal");
+        actionsOut[1] = Input.GetAxis("Vertical");
+    }
+
+    public void SetBall()
+    {
+        //Set the attributes of the ball by fetching the information from the academy
+        m_BallRb.mass = m_ResetParams.GetWithDefault("mass", 1.0f);
+        var scale = m_ResetParams.GetWithDefault("scale", 1.0f);
+        ball.transform.localScale = new Vector3(scale, scale, scale);
+    }
+
+    public void SetResetParameters()
+    {
+        SetBall();
+        // Get agent parameters
+        Debug.Log(GetParameterWithDefault("test_param", 0));
+    }
+}

Project/Assets/ML-Agents/Examples/3DBall/Scripts/Task3DAgent.cs.meta

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

+using Unity.MLAgents.Sensors;
+
+
+public class TaskSensorComponent : SensorComponent
+{
+    public int observationSize;
+    public TaskSensor task_sensor;
+    /// <summary>
+    /// Creates a TaskSensor.
+    /// </summary>
+    /// <returns></returns>
+    public override ISensor CreateSensor()
+    {
+        task_sensor = new TaskSensor(observationSize);
+        return task_sensor;
+    }
+
+    /// <inheritdoc/>
+    public override int[] GetObservationShape()
+    {
+        return new[] { observationSize };
+    }
+
+    public void AddParameterizaton(float parameter)
+    {
+        if(task_sensor != null)
+        {
+            task_sensor.AddObservation(parameter);
+        }
+    }
+}
+
+public class TaskSensor : VectorSensor
+{
+
+    public TaskSensor(int observationSize, string name = null) : base(observationSize)
+    {
+        if (name == null)
+        {
+            name = $"TaskSensor_size{observationSize}";
+        }
+    }
+
+    public override SensorType GetSensorType()
+    {
+        return SensorType.Parameterization;
+    }
+}

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

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com.unity.ml-agents/Runtime/AgentParameters.cs

+using System;
+using System.Collections.Generic;
+using Unity.MLAgents.SideChannels;
+
+namespace Unity.MLAgents
+{
+    /// <summary>
+    /// A container for the Environment Parameters that may be modified during training.
+    /// The keys for those parameters are defined in the trainer configurations and the
+    /// the values are generated from the training process in features such as Curriculum Learning
+    /// and Environment Parameter Randomization.
+    ///
+    /// One current assumption for all the environment parameters is that they are of type float.
+    /// </summary>
+    public sealed class AgentParameters
+    {
+        /// <summary>
+        /// The side channel that is used to receive the new parameter values.
+        /// </summary>
+        readonly AgentParametersChannel m_Channel;
+
+        /// <summary>
+        /// Constructor.
+        /// </summary>
+        internal AgentParameters()