add base team manager

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

         /// </summary>
         public int episodeId;
 
+        /// <summary>
+        /// Team Manager identifier.
+        /// </summary>
+        public int teamManagerId;
+
         public void ClearActions()
         {
             storedActions.Clear();
         /// </summary>
         float[] m_LegacyHeuristicCache;
 
+        ITeamManager m_TeamManager;
+
         /// <summary>
         /// Called when the attached [GameObject] becomes enabled and active.
         /// [GameObject]: https://docs.unity3d.com/Manual/GameObjects.html
                 new float[m_ActuatorManager.NumContinuousActions],
                 new int[m_ActuatorManager.NumDiscreteActions]
             );
+
+            m_Info.teamManagerId = m_TeamManager == null ? -1 : m_TeamManager.GetId();
 
             // The first time the Academy resets, all Agents in the scene will be
             // forced to reset through the <see cref="AgentForceReset"/> event.
             m_Info.reward = m_Reward;
             m_Info.done = true;
             m_Info.maxStepReached = doneReason == DoneReason.MaxStepReached;
+            m_Info.teamManagerId = m_TeamManager == null ? -1 : m_TeamManager.GetId();
             if (collectObservationsSensor != null)
             {
                 // Make sure the latest observations are being passed to training.
             m_Info.done = false;
             m_Info.maxStepReached = false;
             m_Info.episodeId = m_EpisodeId;
+            m_Info.teamManagerId = m_TeamManager == null ? -1 : m_TeamManager.GetId();
 
             using (TimerStack.Instance.Scoped("RequestDecision"))
             {
             var actions = m_Brain?.DecideAction() ?? new ActionBuffers();
             m_Info.CopyActions(actions);
             m_ActuatorManager.UpdateActions(actions);
+        }
+
+        public void SetTeamManager(ITeamManager teamManager)
+        {
+            m_TeamManager = teamManager;
+            teamManager?.RegisterAgent(this);
         }
     }
 }

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

                 MaxStepReached = ai.maxStepReached,
                 Done = ai.done,
                 Id = ai.episodeId,
+                TeamManagerId = ai.teamManagerId,
             };
 
             if (ai.discreteActionMasks != null)

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

           string.Concat(
             "CjNtbGFnZW50c19lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL2FnZW50X2lu",
             "Zm8ucHJvdG8SFGNvbW11bmljYXRvcl9vYmplY3RzGjRtbGFnZW50c19lbnZz",
-            "L2NvbW11bmljYXRvcl9vYmplY3RzL29ic2VydmF0aW9uLnByb3RvItEBCg5B",
+            "L2NvbW11bmljYXRvcl9vYmplY3RzL29ic2VydmF0aW9uLnByb3RvIuoBCg5B",
-            "YXRvcl9vYmplY3RzLk9ic2VydmF0aW9uUHJvdG9KBAgBEAJKBAgCEANKBAgD",
-            "EARKBAgEEAVKBAgFEAZKBAgGEAdKBAgMEA1CJaoCIlVuaXR5Lk1MQWdlbnRz",
-            "LkNvbW11bmljYXRvck9iamVjdHNiBnByb3RvMw=="));
+            "YXRvcl9vYmplY3RzLk9ic2VydmF0aW9uUHJvdG8SFwoPdGVhbV9tYW5hZ2Vy",
+            "X2lkGA4gASgFSgQIARACSgQIAhADSgQIAxAESgQIBBAFSgQIBRAGSgQIBhAH",
+            "SgQIDBANQiWqAiJVbml0eS5NTEFnZW50cy5Db21tdW5pY2F0b3JPYmplY3Rz",
+            "YgZwcm90bzM="));
-            new pbr::GeneratedClrTypeInfo(typeof(global::Unity.MLAgents.CommunicatorObjects.AgentInfoProto), global::Unity.MLAgents.CommunicatorObjects.AgentInfoProto.Parser, new[]{ "Reward", "Done", "MaxStepReached", "Id", "ActionMask", "Observations" }, null, null, null)
+            new pbr::GeneratedClrTypeInfo(typeof(global::Unity.MLAgents.CommunicatorObjects.AgentInfoProto), global::Unity.MLAgents.CommunicatorObjects.AgentInfoProto.Parser, new[]{ "Reward", "Done", "MaxStepReached", "Id", "ActionMask", "Observations", "TeamManagerId" }, null, null, null)
           }));
     }
     #endregion
       id_ = other.id_;
       actionMask_ = other.actionMask_.Clone();
       observations_ = other.observations_.Clone();
+      teamManagerId_ = other.teamManagerId_;
       _unknownFields = pb::UnknownFieldSet.Clone(other._unknownFields);
     }
 
       get { return observations_; }
     }
 
+    /// <summary>Field number for the "team_manager_id" field.</summary>
+    public const int TeamManagerIdFieldNumber = 14;
+    private int teamManagerId_;
+    [global::System.Diagnostics.DebuggerNonUserCodeAttribute]
+    public int TeamManagerId {
+      get { return teamManagerId_; }
+      set {
+        teamManagerId_ = value;
+      }
+    }
+
     [global::System.Diagnostics.DebuggerNonUserCodeAttribute]
     public override bool Equals(object other) {
       return Equals(other as AgentInfoProto);
       if (Id != other.Id) return false;
       if(!actionMask_.Equals(other.actionMask_)) return false;
       if(!observations_.Equals(other.observations_)) return false;
+      if (TeamManagerId != other.TeamManagerId) return false;
       return Equals(_unknownFields, other._unknownFields);
     }
 
       if (Id != 0) hash ^= Id.GetHashCode();
       hash ^= actionMask_.GetHashCode();
       hash ^= observations_.GetHashCode();
+      if (TeamManagerId != 0) hash ^= TeamManagerId.GetHashCode();
       if (_unknownFields != null) {
         hash ^= _unknownFields.GetHashCode();
       }
       }
       actionMask_.WriteTo(output, _repeated_actionMask_codec);
       observations_.WriteTo(output, _repeated_observations_codec);
+      if (TeamManagerId != 0) {
+        output.WriteRawTag(112);
+        output.WriteInt32(TeamManagerId);
+      }
       if (_unknownFields != null) {
         _unknownFields.WriteTo(output);
       }
       }
       size += actionMask_.CalculateSize(_repeated_actionMask_codec);
       size += observations_.CalculateSize(_repeated_observations_codec);
+      if (TeamManagerId != 0) {
+        size += 1 + pb::CodedOutputStream.ComputeInt32Size(TeamManagerId);
+      }
       if (_unknownFields != null) {
         size += _unknownFields.CalculateSize();
       }
       }
       actionMask_.Add(other.actionMask_);
       observations_.Add(other.observations_);
+      if (other.TeamManagerId != 0) {
+        TeamManagerId = other.TeamManagerId;
+      }
       _unknownFields = pb::UnknownFieldSet.MergeFrom(_unknownFields, other._unknownFields);
     }
 
           }
           case 106: {
             observations_.AddEntriesFrom(input, _repeated_observations_codec);
+            break;
+          }
+          case 112: {
+            TeamManagerId = input.ReadInt32();
             break;
           }
         }

ml-agents-envs/mlagents_envs/base_env.py

     reward: float
     agent_id: AgentId
     action_mask: Optional[List[np.ndarray]]
+    team_manager_id: int
 
 
 class DecisionSteps(Mapping):
      this simulation step.
     """
 
-    def __init__(self, obs, reward, agent_id, action_mask):
+    def __init__(self, obs, reward, agent_id, action_mask, team_manager_id):
+        self.team_manager_id: np.ndarray = team_manager_id
         self._agent_id_to_index: Optional[Dict[AgentId, int]] = None
 
     @property
             agent_mask = []
             for mask in self.action_mask:
                 agent_mask.append(mask[agent_index])
+        team_manager_id = self.team_manager_id[agent_index]
+            team_manager_id=team_manager_id,
         )
 
     def __iter__(self) -> Iterator[Any]:
             reward=np.zeros(0, dtype=np.float32),
             agent_id=np.zeros(0, dtype=np.int32),
             action_mask=None,
+            team_manager_id=np.zeros(0, dtype=np.int32),
         )
 
 
     reward: float
     interrupted: bool
     agent_id: AgentId
+    team_manager_id: int
 
 
 class TerminalSteps(Mapping):
      across simulation steps.
     """
 
-    def __init__(self, obs, reward, interrupted, agent_id):
+    def __init__(self, obs, reward, interrupted, agent_id, team_manager_id):
+        self.team_manager_id: np.ndarray = team_manager_id
         self._agent_id_to_index: Optional[Dict[AgentId, int]] = None
 
     @property
         agent_obs = []
         for batched_obs in self.obs:
             agent_obs.append(batched_obs[agent_index])
+        team_manager_id = self.team_manager_id[agent_index]
+            team_manager_id=team_manager_id,
         )
 
     def __iter__(self) -> Iterator[Any]:
             reward=np.zeros(0, dtype=np.float32),
             interrupted=np.zeros(0, dtype=np.bool),
             agent_id=np.zeros(0, dtype=np.int32),
+            team_manager_id=np.zeros(0, dtype=np.int32),
         )
 
 

ml-agents-envs/mlagents_envs/communicator_objects/agent_info_pb2.py

   name='mlagents_envs/communicator_objects/agent_info.proto',
   package='communicator_objects',
   syntax='proto3',
-  serialized_pb=_b('\n3mlagents_envs/communicator_objects/agent_info.proto\x12\x14\x63ommunicator_objects\x1a\x34mlagents_envs/communicator_objects/observation.proto\"\xd1\x01\n\x0e\x41gentInfoProto\x12\x0e\n\x06reward\x18\x07 \x01(\x02\x12\x0c\n\x04\x64one\x18\x08 \x01(\x08\x12\x18\n\x10max_step_reached\x18\t \x01(\x08\x12\n\n\x02id\x18\n \x01(\x05\x12\x13\n\x0b\x61\x63tion_mask\x18\x0b \x03(\x08\x12<\n\x0cobservations\x18\r \x03(\x0b\x32&.communicator_objects.ObservationProtoJ\x04\x08\x01\x10\x02J\x04\x08\x02\x10\x03J\x04\x08\x03\x10\x04J\x04\x08\x04\x10\x05J\x04\x08\x05\x10\x06J\x04\x08\x06\x10\x07J\x04\x08\x0c\x10\rB%\xaa\x02\"Unity.MLAgents.CommunicatorObjectsb\x06proto3')
+  serialized_pb=_b('\n3mlagents_envs/communicator_objects/agent_info.proto\x12\x14\x63ommunicator_objects\x1a\x34mlagents_envs/communicator_objects/observation.proto\"\xea\x01\n\x0e\x41gentInfoProto\x12\x0e\n\x06reward\x18\x07 \x01(\x02\x12\x0c\n\x04\x64one\x18\x08 \x01(\x08\x12\x18\n\x10max_step_reached\x18\t \x01(\x08\x12\n\n\x02id\x18\n \x01(\x05\x12\x13\n\x0b\x61\x63tion_mask\x18\x0b \x03(\x08\x12<\n\x0cobservations\x18\r \x03(\x0b\x32&.communicator_objects.ObservationProto\x12\x17\n\x0fteam_manager_id\x18\x0e \x01(\x05J\x04\x08\x01\x10\x02J\x04\x08\x02\x10\x03J\x04\x08\x03\x10\x04J\x04\x08\x04\x10\x05J\x04\x08\x05\x10\x06J\x04\x08\x06\x10\x07J\x04\x08\x0c\x10\rB%\xaa\x02\"Unity.MLAgents.CommunicatorObjectsb\x06proto3')
   ,
   dependencies=[mlagents__envs_dot_communicator__objects_dot_observation__pb2.DESCRIPTOR,])
 
       message_type=None, enum_type=None, containing_type=None,
       is_extension=False, extension_scope=None,
       options=None, file=DESCRIPTOR),
+    _descriptor.FieldDescriptor(
+      name='team_manager_id', full_name='communicator_objects.AgentInfoProto.team_manager_id', index=6,
+      number=14, type=5, cpp_type=1, 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=[
   ],
   oneofs=[
   ],
   serialized_start=132,
-  serialized_end=341,
+  serialized_end=366,
 )
 
 _AGENTINFOPROTO.fields_by_name['observations'].message_type = mlagents__envs_dot_communicator__objects_dot_observation__pb2._OBSERVATIONPROTO

ml-agents-envs/mlagents_envs/communicator_objects/agent_info_pb2.pyi

     max_step_reached = ... # type: builtin___bool
     id = ... # type: builtin___int
     action_mask = ... # type: google___protobuf___internal___containers___RepeatedScalarFieldContainer[builtin___bool]
+    team_manager_id = ... # type: builtin___int
 
     @property
     def observations(self) -> google___protobuf___internal___containers___RepeatedCompositeFieldContainer[mlagents_envs___communicator_objects___observation_pb2___ObservationProto]: ...
         id : typing___Optional[builtin___int] = None,
         action_mask : typing___Optional[typing___Iterable[builtin___bool]] = None,
         observations : typing___Optional[typing___Iterable[mlagents_envs___communicator_objects___observation_pb2___ObservationProto]] = None,
+        team_manager_id : typing___Optional[builtin___int] = None,
         ) -> None: ...
     @classmethod
     def FromString(cls, s: builtin___bytes) -> AgentInfoProto: ...
-        def ClearField(self, field_name: typing_extensions___Literal[u"action_mask",u"done",u"id",u"max_step_reached",u"observations",u"reward"]) -> None: ...
+        def ClearField(self, field_name: typing_extensions___Literal[u"action_mask",u"done",u"id",u"max_step_reached",u"observations",u"reward",u"team_manager_id"]) -> None: ...
-        def ClearField(self, field_name: typing_extensions___Literal[u"action_mask",b"action_mask",u"done",b"done",u"id",b"id",u"max_step_reached",b"max_step_reached",u"observations",b"observations",u"reward",b"reward"]) -> None: ...
+        def ClearField(self, field_name: typing_extensions___Literal[u"action_mask",b"action_mask",u"done",b"done",u"id",b"id",u"max_step_reached",b"max_step_reached",u"observations",b"observations",u"reward",b"reward",u"team_manager_id",b"team_manager_id"]) -> None: ...

ml-agents-envs/mlagents_envs/rpc_utils.py

         [agent_info.reward for agent_info in terminal_agent_info_list], dtype=np.float32
     )
 
+    decision_team_managers = [
+        agent_info.team_manager_id for agent_info in decision_agent_info_list
+    ]
+    terminal_team_managers = [
+        agent_info.team_manager_id for agent_info in terminal_agent_info_list
+    ]
+
     _raise_on_nan_and_inf(decision_rewards, "rewards")
     _raise_on_nan_and_inf(terminal_rewards, "rewards")
 
             action_mask = np.split(action_mask, indices, axis=1)
     return (
         DecisionSteps(
-            decision_obs_list, decision_rewards, decision_agent_id, action_mask
+            decision_obs_list,
+            decision_rewards,
+            decision_agent_id,
+            action_mask,
+            decision_team_managers,
-        TerminalSteps(terminal_obs_list, terminal_rewards, max_step, terminal_agent_id),
+        TerminalSteps(
+            terminal_obs_list,
+            terminal_rewards,
+            max_step,
+            terminal_agent_id,
+            terminal_team_managers,
+        ),
     )
 
 

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

     repeated bool action_mask = 11;
     reserved 12; // deprecated CustomObservationProto custom_observation = 12;
     repeated ObservationProto observations = 13;
+    int32 team_manager_id = 14;
 }

com.unity.ml-agents.extensions/Runtime/Teams.meta

+fileFormatVersion: 2
+guid: 77124df6c18c4f669052016b3116147e
+folderAsset: yes
+DefaultImporter:
+  externalObjects: {}
+  userData: 
+  assetBundleName: 
+  assetBundleVariant: 

com.unity.ml-agents/Runtime/Actuators/ITeamManager.cs

+using System.Collections.Generic;
+using Unity.MLAgents.Sensors;
+
+namespace Unity.MLAgents
+{
+    public interface ITeamManager
+    {
+        int GetId();
+
+        void RegisterAgent(Agent agent);
+    }
+}

com.unity.ml-agents/Runtime/Actuators/ITeamManager.cs.meta

+fileFormatVersion: 2
+guid: 8b061f82569af4ffba715297f77a95ab
+MonoImporter:
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+  userData: 
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com.unity.ml-agents/Runtime/TeamManagerIdCounter.cs

+using System.Threading;
+
+namespace Unity.MLAgents
+{
+    internal static class TeamManagerIdCounter
+    {
+        static int s_Counter;
+        public static int GetTeamManagerId()
+        {
+            return Interlocked.Increment(ref s_Counter); ;
+        }
+    }
+}

com.unity.ml-agents/Runtime/TeamManagerIdCounter.cs.meta

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com.unity.ml-agents.extensions/Runtime/Teams/BaseTeamManager.cs.meta

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com.unity.ml-agents.extensions/Runtime/Teams/BaseTeamManager.cs

+namespace Unity.MLAgents.Extensions.Teams
+{
+    public class BaseTeamManager : ITeamManager
+    {
+        readonly int m_Id = TeamManagerIdCounter.GetTeamManagerId();
+
+
+        public virtual void RegisterAgent(Agent agent) { }
+
+        public int GetId()
+        {
+            return m_Id;
+        }
+    }
+}