Merge branch 'master' into develop-gym-wrapper

.circleci/config.yml

   python373:
     docker:
       - image: circleci/python:3.7.3
+  python382:
+    docker:
+      - image: circleci/python:3.8.2
 
 jobs:
   build_python:
       - run:
           name: Install Dependencies
           command: |
+            # Need ruby for search-and-replace
+            sudo apt-get update
+            sudo apt-get install ruby-full
             python3 -m venv venv
             . venv/bin/activate
             pip install --upgrade pip
       directory:
         type: string
         description: Local directory to use for publishing (e.g. ml-agents)
+      username:
+        type: string
+        description: pypi username
+        default: mlagents
+      test_repository_args:
+        type: string
+        description: Optional override repository URL. Only use for tests, leave blank for "real"
+        default: ""
     docker:
       - image: circleci/python:3.6
     steps:
           command: |
             . venv/bin/activate
             cd << parameters.directory >>
-            twine upload -u mlagents -p $PYPI_PASSWORD dist/*
+            twine upload -u << parameters.username >> -p $PYPI_PASSWORD << parameters.test_repository_args >> dist/*
 
 workflows:
   version: 2
           pyversion: 3.7.3
           # Test python 3.7 with the newest supported versions
           pip_constraints: test_constraints_max_tf2_version.txt
+      - build_python:
+          name: python_3.8.2+tf2.2
+          executor: python382
+          pyversion: 3.8.2
+          # Test python 3.8 with the newest edge versions
+          pip_constraints: test_constraints_max_tf2_version.txt
+      # The first deploy jobs are the "real" ones that upload to pypi
-              only: /[0-9]+(\.[0-9]+)*(\.dev[0-9]+)*/
+              # Matches e.g. "release_123"
+              only: /^release_[0-9]+$/
             branches:
               ignore: /.*/
       - deploy:
             tags:
-              only: /[0-9]+(\.[0-9]+)*(\.dev[0-9]+)*/
+              # Matches e.g. "release_123"
+              only: /^release_[0-9]+$/
             branches:
               ignore: /.*/
       - deploy:
             tags:
-              only: /[0-9]+(\.[0-9]+)*(\.dev[0-9]+)*/
+              # Matches e.g. "release_123"
+              only: /^release_[0-9]+$/
+            branches:
+              ignore: /.*/
+      # These deploy jobs upload to the pypi test repo. They have different tag triggers than the real ones.
+      - deploy:
+          name: test deploy ml-agents-envs
+          directory: ml-agents-envs
+          username: mlagents-test
+          test_repository_args: --repository-url https://test.pypi.org/legacy/
+          filters:
+            tags:
+              # Matches e.g. "release_123_test456
+              only: /^release_[0-9]+_test[0-9]+$/
+            branches:
+              ignore: /.*/
+      - deploy:
+          name: test deploy ml-agents
+          directory: ml-agents
+          username: mlagents-test
+          test_repository_args: --repository-url https://test.pypi.org/legacy/
+          filters:
+            tags:
+              # Matches e.g. "release_123_test456
+              only: /^release_[0-9]+_test[0-9]+$/
+            branches:
+              ignore: /.*/
+      - deploy:
+          name: test deploy gym-unity
+          directory: gym-unity
+          username: mlagents-test
+          test_repository_args: --repository-url https://test.pypi.org/legacy/
+          filters:
+            tags:
+              # Matches e.g. "release_123_test456
+              only: /^release_[0-9]+_test[0-9]+$/
             branches:
               ignore: /.*/
   nightly:

.gitignore

-# Tensorflow Model Info
+# Output Artifacts (Legacy)
+# Output Artifacts
+/results
 
 # Training environments
 /envs

.pre-commit-config.yaml

             )$
         args: [--score=n]
 
+- repo: https://github.com/mattlqx/pre-commit-search-and-replace
+  rev: v1.0.3
+  hooks:
+  - id: search-and-replace
+    types: [markdown]
+    exclude: ".*localized.*"
+
-        # markdown-link-check doesn't support multiple files on the commandline, so this hacks around that.
-        # Note that you must install the package separately via npm. For example:
-        #  brew install npm; npm install -g markdown-link-check
-        entry: bash -c 'for i in "$@"; do markdown-link-check -c markdown-link-check.fast.json "$i"; done' --
-        language: system
+        entry: utils/run_markdown_link_check.py
+        language: script
         types: [markdown]
         # Don't check localized files since their target might not be localized.
         exclude: ".*localized.*"
         name: markdown-link-check-full
-        entry: bash -c 'for i in "$@"; do markdown-link-check -c markdown-link-check.full.json "$i"; done' --
-        language: system
+        entry: utils/run_markdown_link_check.py
+        language: script
+        # Don't check localized files since their target might not be localized.
+        # Only run manually, e.g. pre-commit run --hook-stage manual markdown-link-check-full
+        args: [--check-remote]
     -   id: validate-versions
         name: validate library versions
         language: script

.pylintrc

 
     # Using the global statement
     W0603,
+
+    # "Access to a protected member _foo of a client class (protected-access)"
+    W0212

.yamato/com.unity.ml-agents-pack.yml

 pack:
   name: Pack
   agent:
-    type: Unity::VM
-    image: package-ci/ubuntu:stable
-    flavor: b1.large
+    type: Unity::VM::osx
+    image: package-ci/mac:stable
+    flavor: b1.small
-    - npm install upm-ci-utils@stable -g --registry https://api.bintray.com/npm/unity/unity-npm
+    - npm install upm-ci-utils@stable -g --registry https://artifactory.prd.cds.internal.unity3d.com/artifactory/api/npm/upm-npm
     - upm-ci package pack --package-path com.unity.ml-agents
   artifacts:
     packages:

.yamato/com.unity.ml-agents-test.yml

   - version: 2020.1
     coverageOptions: --enable-code-coverage --code-coverage-options 'generateHtmlReport;assemblyFilters:+Unity.ML-Agents'
     minCoveragePct: 72
+  - version: 2020.2
+    coverageOptions: --enable-code-coverage --code-coverage-options 'generateHtmlReport;assemblyFilters:+Unity.ML-Agents'
+    minCoveragePct: 72
+trunk_editor:
+  - version: trunk
+    coverageOptions: --enable-code-coverage --code-coverage-options 'generateHtmlReport;assemblyFilters:+Unity.ML-Agents'
+    minCoveragePct: 72
 test_platforms:
   - name: win
     type: Unity::VM
     flavor: b1.medium
 ---
 
+all_package_tests:
+  name: Run All Combinations of Editors/Platforms Tests
+  dependencies:
+  {% for editor in test_editors %}
+    {% for platform in test_platforms %}
+  - .yamato/com.unity.ml-agents-test.yml#test_{{ platform.name }}_{{ editor.version }}
+    {% endfor %}
+  {% endfor %}
+
+  {% for editor in trunk_editor %}
+    {% for platform in test_platforms %}
+  - .yamato/com.unity.ml-agents-test.yml#test_{{ platform.name }}_{{ editor.version }}
+    {% endfor %}
+  {% endfor %}
+  triggers:
+    cancel_old_ci: true
+    recurring:
+      - branch: master
+        frequency: daily
+
 {% for editor in test_editors %}
   {% for platform in test_platforms %}
 test_{{ platform.name }}_{{ editor.version }}:
     image: {{ platform.image }}
     flavor: {{ platform.flavor}}
   commands:
-    - npm install upm-ci-utils@stable -g --registry https://api.bintray.com/npm/unity/unity-npm
+    - npm install upm-ci-utils@stable -g --registry https://artifactory.prd.cds.internal.unity3d.com/artifactory/api/npm/upm-npm
     - upm-ci package test -u {{ editor.version }} --package-path com.unity.ml-agents {{ editor.coverageOptions }}
     - python ml-agents/tests/yamato/check_coverage_percent.py upm-ci~/test-results/ {{ editor.minCoveragePct }}
   artifacts:
     - .yamato/com.unity.ml-agents-pack.yml#pack
   triggers:
     cancel_old_ci: true
+    {% if platform.name == "mac" %}
+    {% endif %}
+  {% endfor %}
+{% endfor %}
-  {% endfor %}
+{% for editor in trunk_editor %}
+  {% for platform in test_platforms %}
+test_{{ platform.name }}_trunk:
+  name : com.unity.ml-agents test {{ editor.version }} on {{ platform.name }}
+  agent:
+    type: {{ platform.type }}
+    image: {{ platform.image }}
+    flavor: {{ platform.flavor}}
+  commands:
+    - python -m pip install unity-downloader-cli --extra-index-url https://artifactory.eu-cph-1.unityops.net/api/pypi/common-python/simple
+    - unity-downloader-cli -u trunk -c editor --wait --fast
+    - npm install upm-ci-utils@stable -g --registry https://artifactory.prd.cds.internal.unity3d.com/artifactory/api/npm/upm-npm
+    - upm-ci package test -u {{ editor.version }} --package-path com.unity.ml-agents {{ editor.coverageOptions }}
+    - python ml-agents/tests/yamato/check_coverage_percent.py upm-ci~/test-results/ {{ editor.minCoveragePct }}
+  artifacts:
+    logs:
+      paths:
+        - "upm-ci~/test-results/**/*"
+  dependencies:
+    - .yamato/com.unity.ml-agents-pack.yml#pack
+  triggers:
+    cancel_old_ci: true
+    {% endfor %}
   {% endfor %}

Project/Assets/ML-Agents/Editor/Tests/StandaloneBuildTest.cs

 using UnityEngine;
 using UnityEditor.Build.Reporting;
 
-namespace MLAgents
+namespace Unity.MLAgents
-        const string k_outputCommandLineFlag = "--mlagents-build-output-path";
-        const string k_sceneCommandLineFlag = "--mlagents-build-scene-path";
+        const string k_OutputCommandLineFlag = "--mlagents-build-output-path";
+        const string k_SceneCommandLineFlag = "--mlagents-build-scene-path";
 
         public static void BuildStandalonePlayerOSX()
         {
             var args = Environment.GetCommandLineArgs();
             for (var i = 0; i < args.Length - 1; i++)
             {
-                if (args[i] == k_outputCommandLineFlag)
+                if (args[i] == k_OutputCommandLineFlag)
-                else if (args[i] == k_sceneCommandLineFlag)
+                else if (args[i] == k_SceneCommandLineFlag)
                 {
                     scenePath = args[i + 1];
                 }

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

   fileIDToRecycleName:
     11400000: Assets/ML-Agents/Examples/3DBall/Demos/Expert3DBall.demo
   externalObjects: {}
-  userData: ' (MLAgents.Demonstrations.DemonstrationSummary)'
+  userData: ' (Unity.MLAgents.Demonstrations.DemonstrationSummary)'
   assetBundleName: 
   assetBundleVariant: 
   script: {fileID: 11500000, guid: 7bd65ce151aaa4a41a45312543c56be1, type: 3}

Project/Assets/ML-Agents/Examples/3DBall/Demos/Expert3DBallHard.demo.meta

   fileIDToRecycleName:
     11400000: Assets/ML-Agents/Examples/3DBall/Demos/Expert3DBallHard.demo
   externalObjects: {}
-  userData: ' (MLAgents.Demonstrations.DemonstrationSummary)'
+  userData: ' (Unity.MLAgents.Demonstrations.DemonstrationSummary)'
   assetBundleName: 
   assetBundleVariant: 
   script: {fileID: 11500000, guid: 7bd65ce151aaa4a41a45312543c56be1, type: 3}

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

 using UnityEngine;
-using MLAgents;
-using MLAgents.Sensors;
-using MLAgents.SideChannels;
+using Unity.MLAgents;
+using Unity.MLAgents.Sensors;
 
 public class Ball3DAgent : Agent
 {
-    FloatPropertiesChannel m_ResetParams;
+    EnvironmentParameters m_ResetParams;
-        m_ResetParams = SideChannelUtils.GetSideChannel<FloatPropertiesChannel>();
+        m_ResetParams = Academy.Instance.EnvironmentParameters;
         SetResetParameters();
     }
 
     public void SetBall()
     {
         //Set the attributes of the ball by fetching the information from the academy
-        m_BallRb.mass = m_ResetParams.GetPropertyWithDefault("mass", 1.0f);
-        var scale = m_ResetParams.GetPropertyWithDefault("scale", 1.0f);
+        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);
     }
 

Project/Assets/ML-Agents/Examples/3DBall/Scripts/Ball3DHardAgent.cs

 using UnityEngine;
-using MLAgents;
-using MLAgents.Sensors;
-using MLAgents.SideChannels;
+using Unity.MLAgents;
+using Unity.MLAgents.Sensors;
 
 public class Ball3DHardAgent : Agent
 {
-    FloatPropertiesChannel m_ResetParams;
+    EnvironmentParameters m_ResetParams;
-        m_ResetParams = SideChannelUtils.GetSideChannel<FloatPropertiesChannel>();
+        m_ResetParams = Academy.Instance.EnvironmentParameters;
         SetResetParameters();
     }
 
     public void SetBall()
     {
         //Set the attributes of the ball by fetching the information from the academy
-        m_BallRb.mass = m_ResetParams.GetPropertyWithDefault("mass", 1.0f);
-        var scale = m_ResetParams.GetPropertyWithDefault("scale", 1.0f);
+        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);
     }
 

Project/Assets/ML-Agents/Examples/Basic/Demos/ExpertBasic.demo.meta

   fileIDToRecycleName:
     11400000: Assets/ML-Agents/Examples/Basic/Demos/ExpertBasic.demo
   externalObjects: {}
-  userData: ' (MLAgents.Demonstrations.DemonstrationSummary)'
+  userData: ' (Unity.MLAgents.Demonstrations.DemonstrationSummary)'
   assetBundleName: 
   assetBundleVariant: 
   script: {fileID: 11500000, guid: 7bd65ce151aaa4a41a45312543c56be1, type: 3}

Project/Assets/ML-Agents/Examples/Basic/Scripts/BasicController.cs

 using UnityEngine;
-using MLAgents;
+using UnityEngine.SceneManagement;
+using Unity.MLAgents;
+using UnityEngine.Serialization;
 
 /// <summary>
 /// An example of how to use ML-Agents without inheriting from the Agent class.
 {
     public float timeBetweenDecisionsAtInference;
     float m_TimeSinceDecision;
+    [FormerlySerializedAs("m_Position")]
-    public int m_Position;
+    public int position;
     const int k_SmallGoalPosition = 7;
     const int k_LargeGoalPosition = 17;
     public GameObject largeGoal;
 
     Agent m_Agent;
 
+
-        ResetAgent();
+        position = 10;
+        transform.position = new Vector3(position - 10f, 0f, 0f);
+        smallGoal.transform.position = new Vector3(k_SmallGoalPosition - 10f, 0f, 0f);
+        largeGoal.transform.position = new Vector3(k_LargeGoalPosition - 10f, 0f, 0f);
     }
 
     /// <summary>
                 break;
         }
 
-        m_Position += direction;
-        if (m_Position < k_MinPosition) { m_Position = k_MinPosition; }
-        if (m_Position > k_MaxPosition) { m_Position = k_MaxPosition; }
+        position += direction;
+        if (position < k_MinPosition) { position = k_MinPosition; }
+        if (position > k_MaxPosition) { position = k_MaxPosition; }
-        gameObject.transform.position = new Vector3(m_Position - 10f, 0f, 0f);
+        gameObject.transform.position = new Vector3(position - 10f, 0f, 0f);
-        if (m_Position == k_SmallGoalPosition)
+        if (position == k_SmallGoalPosition)
         {
             m_Agent.AddReward(0.1f);
             m_Agent.EndEpisode();
-        if (m_Position == k_LargeGoalPosition)
+        if (position == k_LargeGoalPosition)
         {
             m_Agent.AddReward(1f);
             m_Agent.EndEpisode();
 
     public void ResetAgent()
     {
-        m_Position = 10;
-        smallGoal.transform.position = new Vector3(k_SmallGoalPosition - 10f, 0f, 0f);
-        largeGoal.transform.position = new Vector3(k_LargeGoalPosition - 10f, 0f, 0f);
+        // This is a very inefficient way to reset the scene. Used here for testing.
+        SceneManager.LoadScene(SceneManager.GetActiveScene().name);
+        m_Agent = null; // LoadScene only takes effect at the next Update.
+        // We set the Agent to null to avoid using the Agent before the reload
     }
 
     public void FixedUpdate()
 
     void WaitTimeInference()
     {
+        if (m_Agent == null)
+        {
+            return;
+        }
-            m_Agent.RequestDecision();
+            m_Agent?.RequestDecision();
         }
         else
         {
                 ApplyAction(m_Agent.GetAction());
 
                 m_TimeSinceDecision = 0f;
-                m_Agent.RequestDecision();
+                m_Agent?.RequestDecision();
             }
             else
             {

Project/Assets/ML-Agents/Examples/Basic/Scripts/BasicSensorComponent.cs

 using System;
-using MLAgents.Sensors;
-using UnityEngine.Serialization;
+using Unity.MLAgents.Sensors;
-namespace MLAgentsExamples
+namespace Unity.MLAgentsExamples
 {
     /// <summary>
     /// A simple example of a SensorComponent.
         {
             // One-hot encoding of the position
             Array.Clear(output, 0, output.Length);
-            output[basicController.m_Position] = 1;
+            output[basicController.position] = 1;
         }
 
         /// <inheritdoc/>

Project/Assets/ML-Agents/Examples/Basic/TFModels/Basic.nn

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policy_1/dense/MatMulpolicy_1/addd�����?policy_1/Softmaxpolicy_1/add/ypolicy_1/Mulf�����?policy_1/addpolicy_1/strided_slicepolicy_1/Sum������?policy_1/Mulpolicy_1/Sum/reduction_indicespolicy_1/truedivg�����?policy_1/Mulpolicy_1/Sumpolicy_1/add_2d�����?policy_1/truedivpolicy_1/add_2/ypolicy_1/Log_12r�����?
policy_1/add_2policy_1/concat_2/concat2�����?
policy_1/Log_1action2�����?
policy_1/concat_2/concat@@@���3�?���3�k��8�
>�:���{i��#���Ld�n�<�B$�=6_��ސ��8�þ�Z=��>���;�/�O�>�����q�=VU�����=�l��e,�-X7������xQ>>�K��$>46���a><9�>�(>�(O>�(>�X�<��=�p��D��m��>���(z����x��;W�}J�;~7���:���G���%�=�>	8�<;��ݾ=��U>;H<8B%����Å2���?���=g0ѽ ������$־ڜ^>w����.��c��؟=Tgx�C��;�o:�z���)�=������eٳ>�
f�9ˡ=���<
+���)��R��=/)�<��z>��H�$5���>�����}y��l�>��[��@�;�Ӵ=�0�=8׾T;>яV�?h���>Y�k=��=�꽕!�>5�=PO�~���L�J=��̾�м.�<�W?�;��[.��h���?k�Q���b>�u=�;��+?�<IE�>��>wz�=���	��s�^>��O>�_>Wo�>t����f����%V>��c<B��>�1c�Q�,�j�<=���>�̭��G�$��<��>0m¾����j�x�q��>�Y�=��>�^1=��Ͼ<�<ξTP��}:�j�>C�
>��=��$>J��>ߖ>��>ג�>�
g>�>������7=�|=�J?Q�=��> �j>
�P>-�l>೘�W^�]�)>��w>��=���*X��|�>4��?�X>�]�ώ�M�N��>�>B��8�)`��/=�G�=���>�2�>����>�>�_�>���<}�n��f>`�!��(Q�qr1�C�6��.�>��
>}���%�Ͼ�Ɖ>�ܘ�N��ӶG<f1��d�?0�K>�꾀"k��Ϭ>���>^�?��'�+�e(��s��c��>7���J����&����>��e�D�(=]����q�rJ�>.y>�(����eϪ>�(>;�,==5�/�>S%>2}>n#n=�C=�i>y���d��=��ν�|�8[)���0�=L��
+$�J�:>E�>��.��!��4�y=+r�>�|���t��}����~����>*%��+>0L��fB>[g��	����>>��=$ݽ=މ?>�z@�y
v�L��>�2h>Bl#>L(��#vZ>�ر���<���=s%�>jx?���=
p�<3ś=�5^���>��=�D->��)>)�˽g����s?H���ε�xc���Ҿ �M?hRӾ�D�S��P*,?�Ծ���f#�K��mC&?�(@?Pꬾ�ാ�x�>Z�?J��>��پk���s�u��&�����>] ��鸉���"���@?-r��Ҝ�x���F}���5�>�T�>��+�����(.?���>U���4n�=�w��`�*�$5>q6�>O�Z�=��=�k�=�L�<&q= �u>d#
+=M���&����ꖾy:;>��²{>6ƀ<:�h�G^�������T���1�>N��[�s�� =�:!>o{>4���A䛾lo�� �]>{�v�`n�c=4���f?�>M���0
m>�X>����Ҷ�<'�>����NV����|>�ꑾh�ɾ4#�悞<'K�>�
���~�=HO�>N8B��Ui�K	�=u��=e`?��+�ǟ;���.�?�)�DP\?�-���@�;-�9V\?N�<��\2��5�ؗ'���e?��W?bl+�\�/��5[?��]?�O����A?L?^?�;E�'�
?n�>{�8��)	?��
?��?�Ik?��>�F6�OI����.@?)~?��>��8���?�-?�$@�=�>�>?)�4��_�+���9?��?�?��?��M?L?�7�h�?�<?8�@

?�?G;�vI&�`<�?�B?d��U��s�??o	�>CI
+?ݪ5��?��?��?���
�~��>�=?wC�f��L�W?

Project/Assets/ML-Agents/Examples/Bouncer/Demos/ExpertBouncer.demo.meta

   fileIDToRecycleName:
     11400000: Assets/ML-Agents/Examples/Bouncer/Demos/ExpertBouncer.demo
   externalObjects: {}
-  userData: ' (MLAgents.Demonstrations.DemonstrationSummary)'
+  userData: ' (Unity.MLAgents.Demonstrations.DemonstrationSummary)'
   assetBundleName: 
   assetBundleVariant: 
   script: {fileID: 11500000, guid: 7bd65ce151aaa4a41a45312543c56be1, type: 3}

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

 using UnityEngine;
-using MLAgents;
-using MLAgents.Sensors;
-using MLAgents.SideChannels;
+using Unity.MLAgents;
+using Unity.MLAgents.Sensors;
 
 public class BouncerAgent : Agent
 {
     int m_NumberJumps = 20;
     int m_JumpLeft = 20;
 
-    FloatPropertiesChannel m_ResetParams;
+    EnvironmentParameters m_ResetParams;
 
     public override void Initialize()
     {
-        m_ResetParams = SideChannelUtils.GetSideChannel<FloatPropertiesChannel>();
+        m_ResetParams = Academy.Instance.EnvironmentParameters;
 
         SetResetParameters();
     }
 
     public void SetTargetScale()
     {
-        var targetScale = m_ResetParams.GetPropertyWithDefault("target_scale", 1.0f);
+        var targetScale = m_ResetParams.GetWithDefault("target_scale", 1.0f);
         target.transform.localScale = new Vector3(targetScale, targetScale, targetScale);
     }
 

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

 using UnityEngine;
-using MLAgents;
+using Unity.MLAgents;
 
 public class BouncerTarget : MonoBehaviour
 {

Project/Assets/ML-Agents/Examples/Crawler/Demos/ExpertCrawlerDyn.demo.meta

   fileIDToRecycleName:
     11400000: Assets/ML-Agents/Examples/Crawler/Demos/ExpertCrawlerDyn.demo
   externalObjects: {}
-  userData: ' (MLAgents.Demonstrations.DemonstrationSummary)'
+  userData: ' (Unity.MLAgents.Demonstrations.DemonstrationSummary)'
   assetBundleName: 
   assetBundleVariant: 
   script: {fileID: 11500000, guid: 7bd65ce151aaa4a41a45312543c56be1, type: 3}

Project/Assets/ML-Agents/Examples/Crawler/Demos/ExpertCrawlerSta.demo.meta

   fileIDToRecycleName:
     11400000: Assets/ML-Agents/Examples/Crawler/Demos/ExpertCrawlerSta.demo
   externalObjects: {}
-  userData: ' (MLAgents.Demonstrations.DemonstrationSummary)'
+  userData: ' (Unity.MLAgents.Demonstrations.DemonstrationSummary)'
   assetBundleName: 
   assetBundleVariant: 
   script: {fileID: 11500000, guid: 7bd65ce151aaa4a41a45312543c56be1, type: 3}

Project/Assets/ML-Agents/Examples/Crawler/Scripts/CrawlerAgent.cs

 using UnityEngine;
-using MLAgents;
-using MLAgentsExamples;
-using MLAgents.Sensors;
+using Unity.MLAgents;
+using Unity.MLAgentsExamples;
+using Unity.MLAgents.Sensors;
 
 [RequireComponent(typeof(JointDriveController))] // Required to set joint forces
 public class CrawlerAgent : Agent

Project/Assets/ML-Agents/Examples/FoodCollector/Demos/ExpertFood.demo.meta

   fileIDToRecycleName:
     11400000: Assets/ML-Agents/Examples/FoodCollector/Demos/ExpertFood.demo
   externalObjects: {}
-  userData: ' (MLAgents.Demonstrations.DemonstrationSummary)'
+  userData: ' (Unity.MLAgents.Demonstrations.DemonstrationSummary)'
   assetBundleName: 
   assetBundleVariant: 
   script: {fileID: 11500000, guid: 7bd65ce151aaa4a41a45312543c56be1, type: 3}

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

 using UnityEngine;
-using MLAgents;
-using MLAgents.Sensors;
-using MLAgents.SideChannels;
+using Unity.MLAgents;
+using Unity.MLAgents.Sensors;
 
 public class FoodCollectorAgent : Agent
 {
     public bool contribute;
     public bool useVectorObs;
 
+    EnvironmentParameters m_ResetParams;
 
     public override void Initialize()
     {
-
+        m_ResetParams = Academy.Instance.EnvironmentParameters;
         SetResetParameters();
     }
 
 
     public void SetLaserLengths()
     {
-        m_LaserLength = SideChannelUtils.GetSideChannel<FloatPropertiesChannel>().GetPropertyWithDefault("laser_length", 1.0f);
+        m_LaserLength = m_ResetParams.GetWithDefault("laser_length", 1.0f);
-        float agentScale = SideChannelUtils.GetSideChannel<FloatPropertiesChannel>().GetPropertyWithDefault("agent_scale", 1.0f);
+        float agentScale = m_ResetParams.GetWithDefault("agent_scale", 1.0f);
         gameObject.transform.localScale = new Vector3(agentScale, agentScale, agentScale);
     }
 

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

 using UnityEngine;
-using MLAgentsExamples;
+using Unity.MLAgentsExamples;
 
 public class FoodCollectorArea : Area
 {

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

-using System;
-using MLAgents;
-using MLAgents.SideChannels;
+using Unity.MLAgents;
 
 public class FoodCollectorSettings : MonoBehaviour
 {
     public int totalScore;
     public Text scoreText;
 
-    StatsSideChannel m_statsSideChannel;
+    StatsRecorder m_Recorder;
-        m_statsSideChannel = SideChannelUtils.GetSideChannel<StatsSideChannel>();
+        m_Recorder = Academy.Instance.StatsRecorder;
-    public void EnvironmentReset()
+    void EnvironmentReset()
     {
         ClearObjects(GameObject.FindGameObjectsWithTag("food"));
         ClearObjects(GameObject.FindGameObjectsWithTag("badFood"));
         // need to send every Update() call.
         if ((Time.frameCount % 100)== 0)
         {
-            m_statsSideChannel?.AddStat("TotalScore", totalScore);
+            m_Recorder.Add("TotalScore", totalScore);
         }
     }
 }

Project/Assets/ML-Agents/Examples/GridWorld/Demos/ExpertGrid.demo.meta

 fileFormatVersion: 2
-guid: 3938e0ee1f99e473db8e45d334dfa329
+guid: 0092f2e4aece345aea4730a37eeebf68
-  userData: ' (MLAgents.Demonstrations.DemonstrationSummary)'
+  userData: ' (Unity.MLAgents.Demonstrations.DemonstrationSummary)'
   assetBundleName: 
   assetBundleVariant: 
   script: {fileID: 11500000, guid: 7bd65ce151aaa4a41a45312543c56be1, type: 3}

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

 using System;
 using UnityEngine;
 using System.Linq;
-using MLAgents;
-using MLAgents.Sensors;
+using Unity.MLAgents;
-using MLAgents.SideChannels;
 
 public class GridAgent : Agent
 {
     const int k_Down = 2;
     const int k_Left = 3;
     const int k_Right = 4;
+
+    EnvironmentParameters m_ResetParams;
+
+    public override void Initialize()
+    {
+        m_ResetParams = Academy.Instance.EnvironmentParameters;
+    }
 
     public override void CollectDiscreteActionMasks(DiscreteActionMasker actionMasker)
     {
            // Prevents the agent from picking an action that would make it collide with a wall
             var positionX = (int)transform.position.x;
             var positionZ = (int)transform.position.z;
-            var maxPosition = (int)SideChannelUtils.GetSideChannel<FloatPropertiesChannel>().GetPropertyWithDefault("gridSize", 5f) - 1;
+            var maxPosition = (int)m_ResetParams.GetWithDefault("gridSize", 5f) - 1;
-                actionMasker.SetMask(0, new int[]{ k_Left});
+                actionMasker.SetMask(0, new []{ k_Left});
-                actionMasker.SetMask(0, new int[]{k_Right});
+                actionMasker.SetMask(0, new []{k_Right});
-                actionMasker.SetMask(0, new int[]{k_Down});
+                actionMasker.SetMask(0, new []{k_Down});
-                actionMasker.SetMask(0, new int[]{k_Up});
+                actionMasker.SetMask(0, new []{k_Up});
             }
         }
     }

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

 using System.Collections.Generic;
 using UnityEngine;
 using System.Linq;
-using MLAgents;
-using MLAgents.SideChannels;
+using Unity.MLAgents;
 
 
 public class GridArea : MonoBehaviour
     public int[] players;
 
     public GameObject trueAgent;
-
-    FloatPropertiesChannel m_ResetParameters;
 
     Camera m_AgentCam;
 
 
     Vector3 m_InitialPosition;
 
+    EnvironmentParameters m_ResetParams;
+
-        m_ResetParameters = SideChannelUtils.GetSideChannel<FloatPropertiesChannel>();
+        m_ResetParams = Academy.Instance.EnvironmentParameters;
 
         m_Objects = new[] { goalPref, pitPref };
 
         m_InitialPosition = transform.position;
     }
 
-    public void SetEnvironment()
+    void SetEnvironment()
-        transform.position = m_InitialPosition * (m_ResetParameters.GetPropertyWithDefault("gridSize", 5f) + 1);
+        transform.position = m_InitialPosition * (m_ResetParams.GetWithDefault("gridSize", 5f) + 1);
-        for (var i = 0; i < (int)m_ResetParameters.GetPropertyWithDefault("numObstacles", 1); i++)
+        for (var i = 0; i < (int)m_ResetParams.GetWithDefault("numObstacles", 1); i++)
-        for (var i = 0; i < (int)m_ResetParameters.GetPropertyWithDefault("numGoals", 1f); i++)
+        for (var i = 0; i < (int)m_ResetParams.GetWithDefault("numGoals", 1f); i++)
-        var gridSize = (int)m_ResetParameters.GetPropertyWithDefault("gridSize", 5f);
+        var gridSize = (int)m_ResetParams.GetWithDefault("gridSize", 5f);
         m_Plane.transform.localScale = new Vector3(gridSize / 10.0f, 1f, gridSize / 10.0f);
         m_Plane.transform.localPosition = new Vector3((gridSize - 1) / 2f, -0.5f, (gridSize - 1) / 2f);
         m_Sn.transform.localScale = new Vector3(1, 1, gridSize + 2);
 
     public void AreaReset()
     {
-        var gridSize = (int)m_ResetParameters.GetPropertyWithDefault("gridSize", 5f);
+        var gridSize = (int)m_ResetParams.GetWithDefault("gridSize", 5f);
         foreach (var actor in actorObjs)
         {
             DestroyImmediate(actor);
         {
             numbers.Add(Random.Range(0, gridSize * gridSize));
         }
-        var numbersA = Enumerable.ToArray(numbers);
+        var numbersA = numbers.ToArray();
 
         for (var i = 0; i < players.Length; i++)
         {

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

 using UnityEngine;
-using MLAgents;
-using MLAgents.SideChannels;
+using Unity.MLAgents;
 
 public class GridSettings : MonoBehaviour
 {
     {
-        SideChannelUtils.GetSideChannel<FloatPropertiesChannel>().RegisterCallback("gridSize", f =>
+        Academy.Instance.EnvironmentParameters.RegisterCallback("gridSize", f =>
         {
             MainCamera.transform.position = new Vector3(-(f - 1) / 2f, f * 1.25f, -(f - 1) / 2f);
             MainCamera.orthographicSize = (f + 5f) / 2f;

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

   fileIDToRecycleName:
     11400000: Assets/ML-Agents/Examples/Hallway/Demos/ExpertHallway.demo
   externalObjects: {}
-  userData: ' (MLAgents.Demonstrations.DemonstrationSummary)'
+  userData: ' (Unity.MLAgents.Demonstrations.DemonstrationSummary)'
   assetBundleName: 
   assetBundleVariant: 
   script: {fileID: 11500000, guid: 7bd65ce151aaa4a41a45312543c56be1, type: 3}

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

 using System.Collections;
 using UnityEngine;
-using MLAgents;
-using MLAgents.Sensors;
+using Unity.MLAgents;
+using Unity.MLAgents.Sensors;
 
 public class HallwayAgent : Agent
 {
     {
         if (useVectorObs)
         {
-            sensor.AddObservation(StepCount / (float)maxStep);
+            sensor.AddObservation(StepCount / (float)MaxStep);
         }
     }
 
 
     public override void OnActionReceived(float[] vectorAction)
     {
-        AddReward(-1f / maxStep);
+        AddReward(-1f / MaxStep);
         MoveAgent(vectorAction);
     }
 

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

   fileIDToRecycleName:
     11400000: Assets/ML-Agents/Examples/PushBlock/Demos/ExpertPush.demo
   externalObjects: {}
-  userData: ' (MLAgents.Demonstrations.DemonstrationSummary)'
+  userData: ' (Unity.MLAgents.Demonstrations.DemonstrationSummary)'
   assetBundleName: 
   assetBundleVariant: 
   script: {fileID: 11500000, guid: 7bd65ce151aaa4a41a45312543c56be1, type: 3}

Project/Assets/ML-Agents/Examples/PushBlock/Scripts/PushAgentBasic.cs

 
 using System.Collections;
 using UnityEngine;
-using MLAgents;
-using MLAgents.SideChannels;
+using Unity.MLAgents;
 
 public class PushAgentBasic : Agent
 {
     /// </summary>
     Renderer m_GroundRenderer;
 
+    EnvironmentParameters m_ResetParams;
+
     void Awake()
     {
         m_PushBlockSettings = FindObjectOfType<PushBlockSettings>();
         // Starting material
         m_GroundMaterial = m_GroundRenderer.material;
 
+        m_ResetParams = Academy.Instance.EnvironmentParameters;
+
         SetResetParameters();
     }
 
         MoveAgent(vectorAction);
 
         // Penalty given each step to encourage agent to finish task quickly.
-        AddReward(-1f / maxStep);
+        AddReward(-1f / MaxStep);
     }
 
     public override void Heuristic(float[] actionsOut)
 
     public void SetGroundMaterialFriction()
     {
-        var resetParams = SideChannelUtils.GetSideChannel<FloatPropertiesChannel>();
-
-        groundCollider.material.dynamicFriction = resetParams.GetPropertyWithDefault("dynamic_friction", 0);
-        groundCollider.material.staticFriction = resetParams.GetPropertyWithDefault("static_friction", 0);
+        groundCollider.material.dynamicFriction = m_ResetParams.GetWithDefault("dynamic_friction", 0);
+        groundCollider.material.staticFriction = m_ResetParams.GetWithDefault("static_friction", 0);
-        var resetParams = SideChannelUtils.GetSideChannel<FloatPropertiesChannel>();
-
-        var scale = resetParams.GetPropertyWithDefault("block_scale", 2);
+        var scale = m_ResetParams.GetWithDefault("block_scale", 2);
-        m_BlockRb.drag = resetParams.GetPropertyWithDefault("block_drag", 0.5f);
+        m_BlockRb.drag = m_ResetParams.GetWithDefault("block_drag", 0.5f);
-    public void SetResetParameters()
+    void SetResetParameters()
     {
         SetGroundMaterialFriction();
         SetBlockProperties();

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

   fileIDToRecycleName:
     11400000: Assets/ML-Agents/Examples/Pyramids/Demos/ExpertPyramid.demo
   externalObjects: {}
-  userData: ' (MLAgents.Demonstrations.DemonstrationSummary)'
+  userData: ' (Unity.MLAgents.Demonstrations.DemonstrationSummary)'
   assetBundleName: 
   assetBundleVariant: 
   script: {fileID: 11500000, guid: 7bd65ce151aaa4a41a45312543c56be1, type: 3}

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

 using System.Linq;
 using UnityEngine;
 using Random = UnityEngine.Random;
-using MLAgents;
-using MLAgents.Sensors;
+using Unity.MLAgents;
+using Unity.MLAgents.Sensors;
 
 public class PyramidAgent : Agent
 {
 
     public override void OnActionReceived(float[] vectorAction)
     {
-        AddReward(-1f / maxStep);
+        AddReward(-1f / MaxStep);
         MoveAgent(vectorAction);
     }
 

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

 using UnityEngine;
-using MLAgentsExamples;
+using Unity.MLAgentsExamples;
 
 public class PyramidArea : Area
 {

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

   fileIDToRecycleName:
     11400000: Assets/ML-Agents/Examples/Reacher/Demos/ExpertReacher.demo
   externalObjects: {}
-  userData: ' (MLAgents.Demonstrations.DemonstrationSummary)'
+  userData: ' (Unity.MLAgents.Demonstrations.DemonstrationSummary)'
   assetBundleName: 
   assetBundleVariant: 
   script: {fileID: 11500000, guid: 7bd65ce151aaa4a41a45312543c56be1, type: 3}

Project/Assets/ML-Agents/Examples/Reacher/Scripts/ReacherAgent.cs

 using UnityEngine;
-using MLAgents;
-using MLAgents.Sensors;
-using MLAgents.SideChannels;
+using Unity.MLAgents;
+using Unity.MLAgents.Sensors;
 
 public class ReacherAgent : Agent
 {
     // Frequency of the cosine deviation of the goal along the vertical dimension
     float m_DeviationFreq;
 
+    EnvironmentParameters m_ResetParams;
+
     /// <summary>
     /// Collect the rigidbodies of the reacher in order to resue them for
     /// observations and actions.
         m_RbA = pendulumA.GetComponent<Rigidbody>();
         m_RbB = pendulumB.GetComponent<Rigidbody>();
+
+        m_ResetParams = Academy.Instance.EnvironmentParameters;
 
         SetResetParameters();
     }
 
     public void SetResetParameters()
     {
-        var fp = SideChannelUtils.GetSideChannel<FloatPropertiesChannel>();
-        m_GoalSize = fp.GetPropertyWithDefault("goal_size", 5);
-        m_GoalSpeed = Random.Range(-1f, 1f) * fp.GetPropertyWithDefault("goal_speed", 1);
-        m_Deviation = fp.GetPropertyWithDefault("deviation", 0);
-        m_DeviationFreq = fp.GetPropertyWithDefault("deviation_freq", 0);
+        m_GoalSize = m_ResetParams.GetWithDefault("goal_size", 5);
+        m_GoalSpeed = Random.Range(-1f, 1f) * m_ResetParams.GetWithDefault("goal_speed", 1);
+        m_Deviation = m_ResetParams.GetWithDefault("deviation", 0);
+        m_DeviationFreq = m_ResetParams.GetWithDefault("deviation_freq", 0);
     }
 }

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

 using UnityEngine;
 
-namespace MLAgentsExamples
+namespace Unity.MLAgentsExamples
 {
     public class Area : MonoBehaviour
     {

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

 using UnityEngine;
 
-namespace MLAgentsExamples
+namespace Unity.MLAgentsExamples
 {
     public class CameraFollow : MonoBehaviour
     {

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

 using UnityEngine;
 
-namespace MLAgentsExamples
+namespace Unity.MLAgentsExamples
 {
     public class FlyCamera : MonoBehaviour
     {

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

 using UnityEngine;
-using MLAgents;
+using Unity.MLAgents;
-namespace MLAgentsExamples
+namespace Unity.MLAgentsExamples
 {
     /// <summary>
     /// This class contains logic for locomotion agents with joints which might make contact with the ground.

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

 using System.Collections.Generic;
 using UnityEngine;
 using UnityEngine.Serialization;
-using MLAgents;
+using Unity.MLAgents;
-namespace MLAgentsExamples
+namespace Unity.MLAgentsExamples
 {
     /// <summary>
     /// Used to store relevant information for acting and learning for each body part in agent.

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

 using System;
 using System.Collections.Generic;
 using UnityEngine;
-using Barracuda;
+using Unity.Barracuda;
-using MLAgents;
-using MLAgents.Policies;
+using Unity.MLAgents;
+using Unity.MLAgents.Policies;
-namespace MLAgentsExamples
+namespace Unity.MLAgentsExamples
 {
     /// <summary>
     /// Utility class to allow the NNModel file for an agent to be overriden during inference.
             if (m_MaxEpisodes > 0)
             {
                 // 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.
+                // For Agents that specify MaxStep, also make sure we've gone at least that many steps.
-                if (m_Agent.CompletedEpisodes >= m_MaxEpisodes && m_NumSteps > m_MaxEpisodes * m_Agent.maxStep)
+                if (m_Agent.CompletedEpisodes >= m_MaxEpisodes && m_NumSteps > m_MaxEpisodes * m_Agent.MaxStep)
                 {
                     Application.Quit(0);
                 }
 
             if (!m_BehaviorNameOverrides.ContainsKey(behaviorName))
             {
-                Debug.Log($"No override for behaviorName {behaviorName}");
+                Debug.Log($"No override for BehaviorName {behaviorName}");
                 return null;
             }
 
         {
             m_Agent.LazyInitialize();
             var bp = m_Agent.GetComponent<BehaviorParameters>();
-            var name = bp.behaviorName;
+            var behaviorName = bp.BehaviorName;
-            var nnModel = GetModelForBehaviorName(name);
-            Debug.Log($"Overriding behavior {name} for agent with model {nnModel?.name}");
+            var nnModel = GetModelForBehaviorName(behaviorName);
+            Debug.Log($"Overriding behavior {behaviorName} for agent with model {nnModel?.name}");
-            m_Agent.SetModel($"Override_{name}", nnModel);
+            m_Agent.SetModel($"Override_{behaviorName}", nnModel);
 
         }
     }

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

 using System.Linq;
 using UnityEngine;
 
-namespace MLAgents
+namespace Unity.MLAgents
 {
     /// <summary>
     /// Monitor is used to display information about the Agent within the Unity
             s_TransformCamera = new Dictionary<Transform, Camera>();
         }
 
-        /// <inheritdoc/>
         void OnGUI()
         {
             if (!s_Initialized)

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

 using UnityEngine;
-using MLAgents;
-using MLAgents.SideChannels;
+using Unity.MLAgents;
-namespace MLAgentsExamples
+namespace Unity.MLAgentsExamples
+    /// <summary>
+    /// A helper class for the ML-Agents example scenes to override various
+    /// global settings, and restore them afterwards.
+    /// This can modify some Physics and time-stepping properties, so you
+    /// shouldn't copy it into your project unless you know what you're doing.
+    /// </summary>
     public class ProjectSettingsOverrides : MonoBehaviour
     {
         // Original values
             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); });
+            Academy.Instance.EnvironmentParameters.RegisterCallback("gravity", f => { Physics.gravity = new Vector3(0, -f, 0); });
         }
 
         public void OnDestroy()

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

-using MLAgents.Sensors;
+using Unity.MLAgents.Sensors;
-namespace MLAgentsExamples
+namespace Unity.MLAgentsExamples
 {
     /// <summary>
     /// A simple sensor that provides a number default implementations.
 
         /// <summary>
         /// Default implementation of Write interface. This creates a temporary array,
-        /// calls WriteObservation, and then writes the results to the WriteAdapter.
+        /// calls WriteObservation, and then writes the results to the ObservationWriter.
-        /// <param name="adapter"></param>
+        /// <param name="writer"></param>
-        public virtual int Write(WriteAdapter adapter)
+        public virtual int Write(ObservationWriter writer)
         {
             // TODO reuse buffer for similar agents, don't call GetObservationShape()
             var numFloats = this.ObservationSize();
-            adapter.AddRange(buffer);
+            writer.AddRange(buffer);
 
             return numFloats;
         }

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

 using UnityEngine;
 
-namespace MLAgentsExamples
+namespace Unity.MLAgentsExamples
 {
     /// <summary>
     /// This class contains logic for locomotion agents with joints which might make contact with a target.

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

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   - component: {fileID: 114320493772006642}
   - component: {fileID: 9152743230243588598}
-  - component: {fileID: 5530675298926254831}
   m_Layer: 0
   m_Name: PurpleStriker
   m_TagString: purpleAgent
     vectorActionSize: 030000000300000003000000
     vectorActionDescriptions: []
     vectorActionSpaceType: 0
-  m_Model: {fileID: 11400000, guid: 9d26b71f04a2d4680a68d8de4f6b62e9, type: 3}
+  m_Model: {fileID: 11400000, guid: b0a629580a0ab48a5a774f90ff1fb48b, type: 3}
-  m_BehaviorName: Soccer
+  m_BehaviorName: SoccerTwos
   TeamId: 1
   m_UseChildSensors: 1
 --- !u!114 &114492261207303438
   maxStep: 3000
   team: 0
   area: {fileID: 114559182131992928}
+  position: 2
   agentRb: {fileID: 0}
 --- !u!114 &114320493772006642
 MonoBehaviour:
   DecisionPeriod: 5
   TakeActionsBetweenDecisions: 1
   offsetStep: 0
---- !u!114 &5530675298926254831
-MonoBehaviour:
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-  m_CorrespondingSourceObject: {fileID: 0}
-  m_PrefabInstance: {fileID: 0}
-  m_PrefabAsset: {fileID: 0}
-  m_GameObject: {fileID: 1095606497496374}
-  m_Enabled: 1
-  m_EditorHideFlags: 0
-  m_Script: {fileID: 11500000, guid: 3a6da8f78a394c6ab027688eab81e04d, type: 3}
-  m_Name: 
-  m_EditorClassIdentifier: 
 --- !u!1 &1100217258374548
 GameObject:
   m_ObjectHideFlags: 0
   - component: {fileID: 114850431417842684}
   - component: {fileID: 114516244030127556}
   - component: {fileID: 404683423509059512}
-  - component: {fileID: 2668741801881409108}
   m_Layer: 0
   m_Name: BlueStriker
   m_TagString: blueAgent
     vectorActionSize: 030000000300000003000000
     vectorActionDescriptions: []
     vectorActionSpaceType: 0
-  m_Model: {fileID: 11400000, guid: 9d26b71f04a2d4680a68d8de4f6b62e9, type: 3}
+  m_Model: {fileID: 11400000, guid: b0a629580a0ab48a5a774f90ff1fb48b, type: 3}
-  m_BehaviorName: Soccer
+  m_BehaviorName: SoccerTwos
   TeamId: 0