[Release 18] Update versions and links (#5414)

DevProject/Packages/packages-lock.json

       "depth": 0,
       "source": "local",
       "dependencies": {
-        "com.unity.ml-agents": "2.0.0-exp.1",
+        "com.unity.ml-agents": "2.1.0-exp.1",
         "com.unity.modules.physics": "1.0.0"
       }
     },

Project/Packages/packages-lock.json

       "depth": 0,
       "source": "local",
       "dependencies": {
-        "com.unity.ml-agents": "2.0.0-exp.1",
+        "com.unity.ml-agents": "2.1.0-exp.1",
         "com.unity.modules.physics": "1.0.0"
       }
     },

README.md

 
 # Unity ML-Agents Toolkit
 
-[![docs badge](https://img.shields.io/badge/docs-reference-blue.svg)](https://github.com/Unity-Technologies/ml-agents/tree/release_17_docs/docs/)
+[![docs badge](https://img.shields.io/badge/docs-reference-blue.svg)](https://github.com/Unity-Technologies/ml-agents/tree/release_18_docs/docs/)
 
 [![license badge](https://img.shields.io/badge/license-Apache--2.0-green.svg)](LICENSE)
 
 ## Releases & Documentation
 
 **Our latest, stable release is `Release 17`. Click
-[here](https://github.com/Unity-Technologies/ml-agents/tree/release_17_docs/docs/Readme.md)
+[here](https://github.com/Unity-Technologies/ml-agents/tree/release_18_docs/docs/Readme.md)
 to get started with the latest release of ML-Agents.**
 
 The table below lists all our releases, including our `main` branch which is

colab/Colab_UnityEnvironment_1_Run.ipynb

    },
    "source": [
     "# ML-Agents Open a UnityEnvironment\n",
-    "<img src=\"https://github.com/Unity-Technologies/ml-agents/blob/release_1/docs/images/image-banner.png?raw=true\" align=\"middle\" width=\"435\"/>"
+    "<img src=\"https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/images/image-banner.png?raw=true\" align=\"middle\" width=\"435\"/>"
    ]
   },
   {
     "  import mlagents\n",
     "  print(\"ml-agents already installed\")\n",
     "except ImportError:\n",
-    "  !pip install -q mlagents==0.25.1\n",
+    "  !python -m pip install -q mlagents==0.27.0\n",
     "  print(\"Installed ml-agents\")"
    ],
    "execution_count": null,

colab/Colab_UnityEnvironment_2_Train.ipynb

    },
    "source": [
     "# ML-Agents Q-Learning with GridWorld\n",
-    "<img src=\"https://github.com/Unity-Technologies/ml-agents/blob/release_2/docs/images/gridworld.png?raw=true\" align=\"middle\" width=\"435\"/>"
+    "<img src=\"https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/images/gridworld.png?raw=true\" align=\"middle\" width=\"435\"/>"
    ]
   },
   {
     "  import mlagents\n",
     "  print(\"ml-agents already installed\")\n",
     "except ImportError:\n",
-    "  !pip install -q mlagents==0.25.1\n",
+    "  !python -m pip install -q mlagents==0.27.0\n",
     "  print(\"Installed ml-agents\")"
    ],
    "execution_count": null,
     "id": "pZhVRfdoyPmv"
    },
    "source": [
-    "The [GridWorld](https://github.com/Unity-Technologies/ml-agents/blob/release_2/docs/Learning-Environment-Examples.md#gridworld) Environment is a simple Unity visual environment. The Agent is a blue square in a 3x3 grid that is trying to reach a green __`+`__ while avoiding a red __`x`__.\n",
+    "The [GridWorld](https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/Learning-Environment-Examples.md#gridworld) Environment is a simple Unity visual environment. The Agent is a blue square in a 3x3 grid that is trying to reach a green __`+`__ while avoiding a red __`x`__.\n",
     "\n",
     "The observation is an image obtained by a camera on top of the grid.\n",
     "\n",

colab/Colab_UnityEnvironment_3_SideChannel.ipynb

    },
    "source": [
     "# ML-Agents Use SideChannels\n",
-    "<img src=\"https://raw.githubusercontent.com/Unity-Technologies/ml-agents/release_1/docs/images/3dball_big.png\" align=\"middle\" width=\"435\"/>"
+    "<img src=\"https://raw.githubusercontent.com/Unity-Technologies/ml-agents/release_18_docs/docs/images/3dball_big.png\" align=\"middle\" width=\"435\"/>"
    ]
   },
   {
     "  import mlagents\n",
     "  print(\"ml-agents already installed\")\n",
     "except ImportError:\n",
-    "  !pip install -q mlagents==0.25.1\n",
+    "  !python -m pip install -q mlagents==0.27.0\n",
     "  print(\"Installed ml-agents\")"
    ],
    "execution_count": null,
     "## Side Channel\n",
     "\n",
     "SideChannels are objects that can be passed to the constructor of a UnityEnvironment or the `make()` method of a registry entry to send non Reinforcement Learning related data.\n",
-    "More information available [here](https://github.com/Unity-Technologies/ml-agents/blob/release_1/docs/Python-API.md#communicating-additional-information-with-the-environment)\n",
+    "More information available [here](https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/Python-API.md#communicating-additional-information-with-the-environment)\n",
     "\n",
     "\n",
     "\n"
    },
    "source": [
     "### Engine Configuration SideChannel\n",
-    "The [Engine Configuration Side Channel](https://github.com/Unity-Technologies/ml-agents/blob/release_1/docs/Python-API.md#engineconfigurationchannel) is used to configure how the Unity Engine should run.\n",
+    "The [Engine Configuration Side Channel](https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/Python-API.md#engineconfigurationchannel) is used to configure how the Unity Engine should run.\n",
     "We will use the GridWorld environment to demonstrate how to use the EngineConfigurationChannel."
    ]
   },
    },
    "source": [
     "### Environment Parameters Channel\n",
-    "The [Environment Parameters Side Channel](https://github.com/Unity-Technologies/ml-agents/blob/release_1/docs/Python-API.md#environmentparameters) is used to modify environment parameters during the simulation.\n",
+    "The [Environment Parameters Side Channel](https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/Python-API.md#environmentparameters) is used to modify environment parameters during the simulation.\n",
     "We will use the GridWorld environment to demonstrate how to use the EngineConfigurationChannel."
    ]
   },
    },
    "source": [
     "### Creating your own Side Channels\n",
-    "You can send various kinds of data between a Unity Environment and Python but you will need to [create your own implementation of a Side Channel](https://github.com/Unity-Technologies/ml-agents/blob/release_1/docs/Custom-SideChannels.md#custom-side-channels) for advanced use cases.\n"
+    "You can send various kinds of data between a Unity Environment and Python but you will need to [create your own implementation of a Side Channel](https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/Custom-SideChannels.md#custom-side-channels) for advanced use cases.\n"
    ]
   }
  ]

com.unity.ml-agents.extensions/Documentation~/com.unity.ml-agents.extensions.md

 recommended ways to install the package:
 
 ### Local Installation
-[Clone the repository](https://github.com/Unity-Technologies/ml-agents/tree/release_17_docs/docs/Installation.md#clone-the-ml-agents-toolkit-repository-optional) and follow the
-[Local Installation for Development](https://github.com/Unity-Technologies/ml-agents/tree/release_17_docs/docs/Installation.md#advanced-local-installation-for-development-1)
+[Clone the repository](https://github.com/Unity-Technologies/ml-agents/tree/release_18_docs/docs/Installation.md#clone-the-ml-agents-toolkit-repository-optional) and follow the
+[Local Installation for Development](https://github.com/Unity-Technologies/ml-agents/tree/release_18_docs/docs/Installation.md#advanced-local-installation-for-development-1)
-![Package Manager git URL](https://github.com/Unity-Technologies/ml-agents/blob/release_17_docs/docs/images/unity_package_manager_git_url.png)
+![Package Manager git URL](https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/images/unity_package_manager_git_url.png)
-git+https://github.com/Unity-Technologies/ml-agents.git?path=com.unity.ml-agents.extensions#release_17
+git+https://github.com/Unity-Technologies/ml-agents.git?path=com.unity.ml-agents.extensions#release_18
-"com.unity.ml-agents.extensions": "git+https://github.com/Unity-Technologies/ml-agents.git?path=com.unity.ml-agents.extensions#release_17",
+"com.unity.ml-agents.extensions": "git+https://github.com/Unity-Technologies/ml-agents.git?path=com.unity.ml-agents.extensions#release_18",
 ```
 See [Git dependencies](https://docs.unity3d.com/Manual/upm-git.html#subfolder) for more information. Note that this
 may take several minutes to resolve the packages the first time that you add it.
     - No way to customize the action space of the `InputActuatorComponent`
 
 ## Need Help?
-The main [README](https://github.com/Unity-Technologies/ml-agents/tree/release_17_docs/README.md) contains links for contacting the team or getting support.
+The main [README](https://github.com/Unity-Technologies/ml-agents/tree/release_18_docs/README.md) contains links for contacting the team or getting support.

com.unity.ml-agents.extensions/package.json

 {
   "name": "com.unity.ml-agents.extensions",
   "displayName": "ML Agents Extensions",
-  "version": "0.4.0-preview",
+  "version": "0.5.0-preview",
-    "com.unity.ml-agents": "2.0.0-exp.1",
+    "com.unity.ml-agents": "2.1.0-exp.1",
     "com.unity.modules.physics": "1.0.0"
   }
 }

com.unity.ml-agents/CHANGELOG.md

 and this project adheres to
 [Semantic Versioning](http://semver.org/spec/v2.0.0.html).
 
-## [Unreleased]
-### Major Changes
-#### com.unity.ml-agents / com.unity.ml-agents.extensions (C#)
-#### ml-agents / ml-agents-envs / gym-unity (Python)
-### Minor Changes
-#### com.unity.ml-agents / com.unity.ml-agents.extensions (C#)
-#### ml-agents / ml-agents-envs / gym-unity (Python)
-### Bug Fixes
-#### com.unity.ml-agents / com.unity.ml-agents.extensions (C#)
-#### ml-agents / ml-agents-envs / gym-unity (Python)
-
 
 ## [2.1.0-exp.1] - 2021-06-09
 ### Minor Changes

com.unity.ml-agents/Documentation~/com.unity.ml-agents.md

 
 In Unity 2019.4 or later, open the Package Manager, hit the "+" button, and select "Add package from git URL".
 
-![Package Manager git URL](https://github.com/Unity-Technologies/ml-agents/blob/release_17_docs/docs/images/unity_package_manager_git_url.png)
+![Package Manager git URL](https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/images/unity_package_manager_git_url.png)
-git+https://github.com/Unity-Technologies/ml-agents.git?path=com.unity.ml-agents#release_17
+git+https://github.com/Unity-Technologies/ml-agents.git?path=com.unity.ml-agents#release_18
-"com.unity.ml-agents": "git+https://github.com/Unity-Technologies/ml-agents.git?path=com.unity.ml-agents#release_17",
+"com.unity.ml-agents": "git+https://github.com/Unity-Technologies/ml-agents.git?path=com.unity.ml-agents#release_18",
 ```
 See [Git dependencies](https://docs.unity3d.com/Manual/upm-git.html#subfolder) for more information. Note that this
 may take several minutes to resolve the packages the first time that you add it.
-[Clone the repository](https://github.com/Unity-Technologies/ml-agents/tree/release_17_docs/docs/Installation.md#clone-the-ml-agents-toolkit-repository-optional) and follow the
-[Local Installation for Development](https://github.com/Unity-Technologies/ml-agents/tree/release_17_docs/docs/Installation.md#advanced-local-installation-for-development-1)
+[Clone the repository](https://github.com/Unity-Technologies/ml-agents/tree/release_18_docs/docs/Installation.md#clone-the-ml-agents-toolkit-repository-optional) and follow the
+[Local Installation for Development](https://github.com/Unity-Technologies/ml-agents/tree/release_18_docs/docs/Installation.md#advanced-local-installation-for-development-1)
 directions.
 
 ## Requirements
 [unity ML-Agents Toolkit]: https://github.com/Unity-Technologies/ml-agents
 [unity inference engine]: https://docs.unity3d.com/Packages/com.unity.barracuda@latest/index.html
 [package manager documentation]: https://docs.unity3d.com/Manual/upm-ui-install.html
-[installation instructions]: https://github.com/Unity-Technologies/ml-agents/blob/release_17_docs/docs/Installation.md
+[installation instructions]: https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/Installation.md
-[ML-Agents GitHub repo]: https://github.com/Unity-Technologies/ml-agents/blob/release_17_docs/com.unity.ml-agents.extensions
+[ML-Agents GitHub repo]: https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/com.unity.ml-agents.extensions

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

  * API. For more information on each of these entities, in addition to how to
  * set-up a learning environment and train the behavior of characters in a
  * Unity scene, please browse our documentation pages on GitHub:
- * https://github.com/Unity-Technologies/ml-agents/tree/release_17_docs/docs/
+ * https://github.com/Unity-Technologies/ml-agents/tree/release_18_docs/docs/
  */
 
 namespace Unity.MLAgents
     /// fall back to inference or heuristic decisions. (You can also set agents to always use
     /// inference or heuristics.)
     /// </remarks>
-    [HelpURL("https://github.com/Unity-Technologies/ml-agents/tree/release_17_docs/" +
+    [HelpURL("https://github.com/Unity-Technologies/ml-agents/tree/release_18_docs/" +
         "docs/Learning-Environment-Design.md")]
     public class Academy : IDisposable
     {
         /// Unity package version of com.unity.ml-agents.
         /// This must match the version string in package.json and is checked in a unit test.
         /// </summary>
-        internal const string k_PackageVersion = "2.0.0-exp.1";
+        internal const string k_PackageVersion = "2.1.0-exp.1";
 
         const int k_EditorTrainingPort = 5004;
 

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

         ///
         /// See [Agents - Actions] for more information on masking actions.
         ///
-        /// [Agents - Actions]: https://github.com/Unity-Technologies/ml-agents/blob/release_17_docs/docs/Learning-Environment-Design-Agents.md#actions
+        /// [Agents - Actions]: https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/Learning-Environment-Design-Agents.md#actions
         /// </remarks>
         /// <seealso cref="IActionReceiver.OnActionReceived"/>
         void WriteDiscreteActionMask(IDiscreteActionMask actionMask);

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

         ///
         /// See [Agents - Actions] for more information on masking actions.
         ///
-        /// [Agents - Actions]: https://github.com/Unity-Technologies/ml-agents/blob/release_17_docs/docs/Learning-Environment-Design-Agents.md#masking-discrete-actions
+        /// [Agents - Actions]: https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/Learning-Environment-Design-Agents.md#masking-discrete-actions
         /// </remarks>
         /// <param name="branch">The branch for which the actions will be masked.</param>
         /// <param name="actionIndex">Index of the action.</param>

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

     /// [OnDisable()]: https://docs.unity3d.com/ScriptReference/MonoBehaviour.OnDisable.html]
     /// [OnBeforeSerialize()]: https://docs.unity3d.com/ScriptReference/MonoBehaviour.OnBeforeSerialize.html
     /// [OnAfterSerialize()]: https://docs.unity3d.com/ScriptReference/MonoBehaviour.OnAfterSerialize.html
-    /// [Agents]: https://github.com/Unity-Technologies/ml-agents/blob/release_17_docs/docs/Learning-Environment-Design-Agents.md
-    /// [Reinforcement Learning in Unity]: https://github.com/Unity-Technologies/ml-agents/blob/release_17_docs/docs/Learning-Environment-Design.md
+    /// [Agents]: https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/Learning-Environment-Design-Agents.md
+    /// [Reinforcement Learning in Unity]: https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/Learning-Environment-Design.md
-    /// [Unity ML-Agents Toolkit manual]: https://github.com/Unity-Technologies/ml-agents/blob/release_17_docs/docs/Readme.md
+    /// [Unity ML-Agents Toolkit manual]: https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/Readme.md
-    [HelpURL("https://github.com/Unity-Technologies/ml-agents/blob/release_17_docs/" +
+    [HelpURL("https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/" +
         "docs/Learning-Environment-Design-Agents.md")]
     [Serializable]
     [RequireComponent(typeof(BehaviorParameters))]
         /// for information about mixing reward signals from curiosity and Generative Adversarial
         /// Imitation Learning (GAIL) with rewards supplied through this method.
         ///
-        /// [Agents - Rewards]: https://github.com/Unity-Technologies/ml-agents/blob/release_17_docs/docs/Learning-Environment-Design-Agents.md#rewards
-        /// [Reward Signals]: https://github.com/Unity-Technologies/ml-agents/blob/release_17_docs/docs/ML-Agents-Overview.md#a-quick-note-on-reward-signals
+        /// [Agents - Rewards]: https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/Learning-Environment-Design-Agents.md#rewards
+        /// [Reward Signals]: https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/ML-Agents-Overview.md#a-quick-note-on-reward-signals
         /// </remarks>
         /// <param name="reward">The new value of the reward.</param>
         public void SetReward(float reward)
         /// for information about mixing reward signals from curiosity and Generative Adversarial
         /// Imitation Learning (GAIL) with rewards supplied through this method.
         ///
-        /// [Agents - Rewards]: https://github.com/Unity-Technologies/ml-agents/blob/release_17_docs/docs/Learning-Environment-Design-Agents.md#rewards
-        /// [Reward Signals]: https://github.com/Unity-Technologies/ml-agents/blob/release_17_docs/docs/ML-Agents-Overview.md#a-quick-note-on-reward-signals
+        /// [Agents - Rewards]: https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/Learning-Environment-Design-Agents.md#rewards
+        /// [Reward Signals]: https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/ML-Agents-Overview.md#a-quick-note-on-reward-signals
         ///</remarks>
         /// <param name="increment">Incremental reward value.</param>
         public void AddReward(float increment)
         /// implementing a simple heuristic function can aid in debugging agent actions and interactions
         /// with its environment.
         ///
-        /// [Demonstration Recorder]: https://github.com/Unity-Technologies/ml-agents/blob/release_17_docs/docs/Learning-Environment-Design-Agents.md#recording-demonstrations
-        /// [Actions]: https://github.com/Unity-Technologies/ml-agents/blob/release_17_docs/docs/Learning-Environment-Design-Agents.md#actions
+        /// [Demonstration Recorder]: https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/Learning-Environment-Design-Agents.md#recording-demonstrations
+        /// [Actions]: https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/Learning-Environment-Design-Agents.md#actions
         /// [GameObject]: https://docs.unity3d.com/Manual/GameObjects.html
         /// </remarks>
         /// <example>
         /// For more information about observations, see [Observations and Sensors].
         ///
         /// [GameObject]: https://docs.unity3d.com/Manual/GameObjects.html
-        /// [Observations and Sensors]: https://github.com/Unity-Technologies/ml-agents/blob/release_17_docs/docs/Learning-Environment-Design-Agents.md#observations-and-sensors
+        /// [Observations and Sensors]: https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/Learning-Environment-Design-Agents.md#observations-and-sensors
         /// </remarks>
         public virtual void CollectObservations(VectorSensor sensor)
         {
         ///
         /// See [Agents - Actions] for more information on masking actions.
         ///
-        /// [Agents - Actions]: https://github.com/Unity-Technologies/ml-agents/blob/release_17_docs/docs/Learning-Environment-Design-Agents.md#actions
+        /// [Agents - Actions]: https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/Learning-Environment-Design-Agents.md#actions
         /// </remarks>
         /// <seealso cref="IActionReceiver.OnActionReceived"/>
         public virtual void WriteDiscreteActionMask(IDiscreteActionMask actionMask) { }
         ///
         /// For more information about implementing agent actions see [Agents - Actions].
         ///
-        /// [Agents - Actions]: https://github.com/Unity-Technologies/ml-agents/blob/release_17_docs/docs/Learning-Environment-Design-Agents.md#actions
+        /// [Agents - Actions]: https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/Learning-Environment-Design-Agents.md#actions
         /// </remarks>
         /// <param name="actions">
         /// Struct containing the buffers of actions to be executed at this step.

com.unity.ml-agents/Runtime/Demonstrations/DemonstrationRecorder.cs

     /// See [Imitation Learning - Recording Demonstrations] for more information.
     ///
     /// [GameObject]: https://docs.unity3d.com/Manual/GameObjects.html
-    /// [Imitation Learning - Recording Demonstrations]: https://github.com/Unity-Technologies/ml-agents/blob/release_17_docs/docs//Learning-Environment-Design-Agents.md#recording-demonstrations
+    /// [Imitation Learning - Recording Demonstrations]: https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs//Learning-Environment-Design-Agents.md#recording-demonstrations
     /// </remarks>
     [RequireComponent(typeof(Agent))]
     [AddComponentMenu("ML Agents/Demonstration Recorder", (int)MenuGroup.Default)]

com.unity.ml-agents/package.json

 {
   "name": "com.unity.ml-agents",
   "displayName": "ML Agents",
-  "version": "2.0.0-exp.1",
+  "version": "2.1.0-exp.1",
   "unity": "2019.4",
   "description": "Use state-of-the-art machine learning to create intelligent character behaviors in any Unity environment (games, robotics, film, etc.).",
   "dependencies": {

docs/Installation-Anaconda-Windows.md

 the ml-agents Conda environment by typing `activate ml-agents`)_:
 
 ```sh
-git clone --branch release_17 https://github.com/Unity-Technologies/ml-agents.git
+git clone --branch release_18 https://github.com/Unity-Technologies/ml-agents.git
-The `--branch release_17` option will switch to the tag of the latest stable
+The `--branch release_18` option will switch to the tag of the latest stable
 release. Omitting that will get the `main` branch which is potentially
 unstable.
 
 connected to the Internet and then type in the Anaconda Prompt:
 
 ```console
-python -m pip install mlagents==0.26.0
+python -m pip install mlagents==0.27.0
 ```
 
 This will complete the installation of all the required Python packages to run
 this, you can try:
 
 ```console
-python -m pip install mlagents==0.26.0 --no-cache-dir
+python -m pip install mlagents==0.27.0 --no-cache-dir
 ```
 
 This `--no-cache-dir` tells the pip to disable the cache.

docs/Installation.md

 the repository if you would like to explore more examples.
 
 ```sh
-git clone --branch release_17 https://github.com/Unity-Technologies/ml-agents.git
+git clone --branch release_18 https://github.com/Unity-Technologies/ml-agents.git
-The `--branch release_17` option will switch to the tag of the latest stable
+The `--branch release_18` option will switch to the tag of the latest stable
 release. Omitting that will get the `main` branch which is potentially unstable.
 
 #### Advanced: Local Installation for Development
-back, make sure to clone the `main` branch (by omitting `--branch release_17`
+back, make sure to clone the `main` branch (by omitting `--branch release_18`
 from the command above). See our
 [Contributions Guidelines](../com.unity.ml-agents/CONTRIBUTING.md) for more
 information on contributing to the ML-Agents Toolkit.
 run from the command line:
 
 ```sh
-python -m pip install mlagents==0.26.0
+python -m pip install mlagents==0.27.0
 ```
 
 Note that this will install `mlagents` from PyPi, _not_ from the cloned

docs/Learning-Environment-Design-Agents.md

 `GridSensorComponent` and the underlying `GridSensorBase` also provides interfaces
 that can be overridden to collect customized observation from detected objects.
 See the doc on
-[extending grid Sensors](https://github.com/Unity-Technologies/ml-agents/blob/release_17/com.unity.ml-agents.extensions/Documentation~/CustomGridSensors.md)
+[extending grid Sensors](https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/com.unity.ml-agents.extensions/Documentation~/CustomGridSensors.md)
 for more details on custom grid sensors.
 
 __Note__: The `GridSensor` only works in 3D environments and will not behave

docs/Migrating.md

 - The Parameter Randomization feature has been merged with the Curriculum feature. It is now possible to specify a sampler
 in the lesson of a Curriculum. Curriculum has been refactored and is now specified at the level of the parameter, not the
 behavior. More information
-[here](https://github.com/Unity-Technologies/ml-agents/blob/release_17_docs/docs/Training-ML-Agents.md).(#4160)
+[here](https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/Training-ML-Agents.md).(#4160)
 
 ### Steps to Migrate
 - The configuration format for curriculum and parameter randomization has changed. To upgrade your configuration files,

docs/Readme.md

 
 ## Python Tutorial with Google Colab
 
-- [Using a UnityEnvironment](https://colab.research.google.com/github/Unity-Technologies/ml-agents/blob/main/colab/Colab_UnityEnvironment_1_Run.ipynb)
-- [Q-Learning with a UnityEnvironment](https://colab.research.google.com/github/Unity-Technologies/ml-agents/blob/main/colab/Colab_UnityEnvironment_2_Train.ipynb)
-- [Using Side Channels on a UnityEnvironment](https://colab.research.google.com/github/Unity-Technologies/ml-agents/blob/main/colab/Colab_UnityEnvironment_3_SideChannel.ipynb)
+- [Using a UnityEnvironment](https://colab.research.google.com/github/Unity-Technologies/ml-agents/blob/release_18_docs/colab/Colab_UnityEnvironment_1_Run.ipynb)
+- [Q-Learning with a UnityEnvironment](https://colab.research.google.com/github/Unity-Technologies/ml-agents/blob/release_18_docs/colab/Colab_UnityEnvironment_2_Train.ipynb)
+- [Using Side Channels on a UnityEnvironment](https://colab.research.google.com/github/Unity-Technologies/ml-agents/blob/release_18_docs/colab/Colab_UnityEnvironment_3_SideChannel.ipynb)
 
 ## Help
 

docs/Training-on-Amazon-Web-Service.md

 2. Clone the ML-Agents repo and install the required Python packages
 
    ```sh
-   git clone --branch release_17 https://github.com/Unity-Technologies/ml-agents.git
+   git clone --branch release_18 https://github.com/Unity-Technologies/ml-agents.git
    cd ml-agents/ml-agents/
    pip3 install -e .
    ```

docs/Training-on-Microsoft-Azure.md

    instance, and set it as the working directory.
 2. Install the required packages:
    Torch: `pip3 install torch==1.7.0 -f https://download.pytorch.org/whl/torch_stable.html` and
-   MLAgents: `python -m pip install mlagents==0.26.0`
+   MLAgents: `python -m pip install mlagents==0.27.0`
 
 ## Testing
 

docs/Unity-Inference-Engine.md

 loading expects certain conventions for constants and tensor names. While it is
 possible to construct a model that follows these conventions, we don't provide
 any additional help for this. More details can be found in
-[TensorNames.cs](https://github.com/Unity-Technologies/ml-agents/blob/release_17_docs/com.unity.ml-agents/Runtime/Inference/TensorNames.cs)
+[TensorNames.cs](https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/com.unity.ml-agents/Runtime/Inference/TensorNames.cs)
-[BarracudaModelParamLoader.cs](https://github.com/Unity-Technologies/ml-agents/blob/release_17_docs/com.unity.ml-agents/Runtime/Inference/BarracudaModelParamLoader.cs).
+[BarracudaModelParamLoader.cs](https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/com.unity.ml-agents/Runtime/Inference/BarracudaModelParamLoader.cs).
 
 If you wish to run inference on an externally trained model, you should use
 Barracuda directly, instead of trying to run it through ML-Agents.

gym-unity/gym_unity/__init__.py

 # Version of the library that will be used to upload to pypi
-__version__ = "0.27.0.dev0"
+__version__ = "0.27.0"
-__release_tag__ = None
+__release_tag__ = "release_18"

ml-agents-envs/README.md

 Install the `mlagents_envs` package with:
 
 ```sh
-python -m pip install mlagents_envs==0.26.0
+python -m pip install mlagents_envs==0.27.0
 ```
 
 ## Usage & More Information

ml-agents-envs/mlagents_envs/__init__.py

 # Version of the library that will be used to upload to pypi
-__version__ = "0.27.0.dev0"
+__version__ = "0.27.0"
-__release_tag__ = None
+__release_tag__ = "release_18"

ml-agents/README.md

 Install the `mlagents` package with:
 
 ```sh
-python -m pip install mlagents==0.26.0
+python -m pip install mlagents==0.27.0
 ```
 
 ## Usage & More Information

ml-agents/mlagents/trainers/__init__.py

 # Version of the library that will be used to upload to pypi
-__version__ = "0.27.0.dev0"
+__version__ = "0.27.0"
-__release_tag__ = None
+__release_tag__ = "release_18"

ml-agents/setup.py

         "protobuf>=3.6",
         "pyyaml>=3.1.0",
         # Windows ver. of PyTorch doesn't work from PyPi. Installation:
-        # https://github.com/Unity-Technologies/ml-agents/blob/release_17_docs/docs/Installation.md#windows-installing-pytorch
+        # https://github.com/Unity-Technologies/ml-agents/blob/release_18_docs/docs/Installation.md#windows-installing-pytorch
         # Torch only working on python 3.9 for 1.8.0 and above. Details see:
         # https://github.com/pytorch/pytorch/issues/50014
         "torch>=1.8.0,<1.9.0;(platform_system!='Windows' and python_version>='3.9')",

utils/validate_release_links.py

     match = PIP_INSTALL_PATTERN.search(line)
     if match is not None:  # if there is a pip install line
         package_name = match.group("package")
-        quiet_option = match.group("quiet")
+        quiet_option = match.group("quiet") or ""
         replacement_version = (
             f"python -m pip install {quiet_option}{package_name}=={package_verion}"
         )