Update versions and release strings (#4289)

Co-authored-by: Chris Elion <chris.elion@unity3d.com>

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_4_docs/docs/)
+[![docs badge](https://img.shields.io/badge/docs-reference-blue.svg)](https://github.com/Unity-Technologies/ml-agents/tree/release_5_docs/docs/)
 
 [![license badge](https://img.shields.io/badge/license-Apache--2.0-green.svg)](LICENSE)
 
 
 ## Releases & Documentation
 
-**Our latest, stable release is `Release 4`. Click
-[here](https://github.com/Unity-Technologies/ml-agents/tree/release_4_docs/docs/Readme.md)
+**Our latest, stable release is `Release 5`. Click
+[here](https://github.com/Unity-Technologies/ml-agents/tree/release_5_docs/docs/Readme.md)
 to get started with the latest release of ML-Agents.**
 
 The table below lists all our releases, including our `master` branch which is
   instructions specific to each release. Remember to always use the
   documentation that corresponds to the release version you're using.
 
-| **Version** | **Release Date** | **Source** | **Documentation** | **Download** |
-|:-------:|:------:|:-------------:|:-------:|:------------:|
-| **Release 4** | **July 15, 2020** | **[source](https://github.com/Unity-Technologies/ml-agents/tree/release_4)** | **[docs](https://github.com/Unity-Technologies/ml-agents/tree/release_4_docs/docs/Readme.md)** | **[download](https://github.com/Unity-Technologies/ml-agents/archive/release_4.zip)** |
+| **Release 5** | **July 31, 2020** | **[source](https://github.com/Unity-Technologies/ml-agents/tree/release_5)** | **[docs](https://github.com/Unity-Technologies/ml-agents/tree/release_5_docs/docs/Readme.md)** | **[download](https://github.com/Unity-Technologies/ml-agents/archive/release_5.zip)** |
+| **Release 4** | July 15, 2020 | [source](https://github.com/Unity-Technologies/ml-agents/tree/release_4) | [docs](https://github.com/Unity-Technologies/ml-agents/tree/release_4_docs/docs/Readme.md) | [download](https://github.com/Unity-Technologies/ml-agents/archive/release_4.zip) |
-| **0.14.1** | February 26, 2020 | [source](https://github.com/Unity-Technologies/ml-agents/tree/0.14.1) | [docs](https://github.com/Unity-Technologies/ml-agents/tree/0.14.1/docs/Readme.md) | [download](https://github.com/Unity-Technologies/ml-agents/archive/0.14.1.zip) |
 
 ## Citation
 

com.unity.ml-agents/CHANGELOG.md

 - `max_step` in the `TerminalStep` and `TerminalSteps` objects was renamed `interrupted`.
 - `beta` and `epsilon` in `PPO` are no longer decayed by default but follow the same schedule as learning rate. (#3940)
 - `get_behavior_names()` and `get_behavior_spec()` on UnityEnvironment were replaced by the `behavior_specs` property. (#3946)
-- The first version of the Unity Environment Registry (Experimental) has been released. More information [here](https://github.com/Unity-Technologies/ml-agents/blob/release_4_docs/docs/Unity-Environment-Registry.md)(#3967)
+- The first version of the Unity Environment Registry (Experimental) has been released. More information [here](https://github.com/Unity-Technologies/ml-agents/blob/release_5_docs/docs/Unity-Environment-Registry.md)(#3967)
 - `use_visual` and `allow_multiple_visual_obs` in the `UnityToGymWrapper` constructor
 were replaced by `allow_multiple_obs` which allows one or more visual observations and
 vector observations to be used simultaneously. (#3981) Thank you @shakenes !
 - The format for trainer configuration has changed, and the "default" behavior has been deprecated.
-  See the [Migration Guide](https://github.com/Unity-Technologies/ml-agents/blob/release_4_docs/docs/Migrating.md) for more details. (#3936)
+  See the [Migration Guide](https://github.com/Unity-Technologies/ml-agents/blob/release_5_docs/docs/Migrating.md) for more details. (#3936)
 - Training artifacts (trained models, summaries) are now found in the `results/`
   directory. (#3829)
 - When using Curriculum, the current lesson will resume if training is quit and resumed. As such,

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

 [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_4_docs/docs/Installation.md
+[installation instructions]: https://github.com/Unity-Technologies/ml-agents/blob/release_5_docs/docs/Installation.md
 [github repository]: https://github.com/Unity-Technologies/ml-agents
 [python package]: https://github.com/Unity-Technologies/ml-agents
 [execution order of event functions]: https://docs.unity3d.com/Manual/ExecutionOrder.html

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_4_docs/docs/
+ * https://github.com/Unity-Technologies/ml-agents/tree/release_5_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_4_docs/" +
+    [HelpURL("https://github.com/Unity-Technologies/ml-agents/tree/release_5_docs/" +
         "docs/Learning-Environment-Design.md")]
     public class Academy : IDisposable
     {

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_4_docs/docs/Learning-Environment-Design-Agents.md
-    /// [Reinforcement Learning in Unity]: https://github.com/Unity-Technologies/ml-agents/blob/release_4_docs/docs/Learning-Environment-Design.md
+    /// [Agents]: https://github.com/Unity-Technologies/ml-agents/blob/release_5_docs/docs/Learning-Environment-Design-Agents.md
+    /// [Reinforcement Learning in Unity]: https://github.com/Unity-Technologies/ml-agents/blob/release_5_docs/docs/Learning-Environment-Design.md
-    /// [Unity ML-Agents Toolkit manual]: https://github.com/Unity-Technologies/ml-agents/blob/release_4_docs/docs/Readme.md
+    /// [Unity ML-Agents Toolkit manual]: https://github.com/Unity-Technologies/ml-agents/blob/release_5_docs/docs/Readme.md
-    [HelpURL("https://github.com/Unity-Technologies/ml-agents/blob/release_4_docs/" +
+    [HelpURL("https://github.com/Unity-Technologies/ml-agents/blob/release_5_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_4_docs/docs/Learning-Environment-Design-Agents.md#rewards
-        /// [Reward Signals]: https://github.com/Unity-Technologies/ml-agents/blob/release_4_docs/docs/ML-Agents-Overview.md#a-quick-note-on-reward-signals
+        /// [Agents - Rewards]: https://github.com/Unity-Technologies/ml-agents/blob/release_5_docs/docs/Learning-Environment-Design-Agents.md#rewards
+        /// [Reward Signals]: https://github.com/Unity-Technologies/ml-agents/blob/release_5_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_4_docs/docs/Learning-Environment-Design-Agents.md#rewards
-        /// [Reward Signals]: https://github.com/Unity-Technologies/ml-agents/blob/release_4_docs/docs/ML-Agents-Overview.md#a-quick-note-on-reward-signals
+        /// [Agents - Rewards]: https://github.com/Unity-Technologies/ml-agents/blob/release_5_docs/docs/Learning-Environment-Design-Agents.md#rewards
+        /// [Reward Signals]: https://github.com/Unity-Technologies/ml-agents/blob/release_5_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_4_docs/docs/Learning-Environment-Design-Agents.md#recording-demonstrations
-        /// [Actions]: https://github.com/Unity-Technologies/ml-agents/blob/release_4_docs/docs/Learning-Environment-Design-Agents.md#actions
+        /// [Demonstration Recorder]: https://github.com/Unity-Technologies/ml-agents/blob/release_5_docs/docs/Learning-Environment-Design-Agents.md#recording-demonstrations
+        /// [Actions]: https://github.com/Unity-Technologies/ml-agents/blob/release_5_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_4_docs/docs/Learning-Environment-Design-Agents.md#observations-and-sensors
+        /// [Observations and Sensors]: https://github.com/Unity-Technologies/ml-agents/blob/release_5_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_4_docs/docs/Learning-Environment-Design-Agents.md#actions
+        /// [Agents - Actions]: https://github.com/Unity-Technologies/ml-agents/blob/release_5_docs/docs/Learning-Environment-Design-Agents.md#actions
         /// </remarks>
         /// <seealso cref="OnActionReceived(float[])"/>
         public virtual void CollectDiscreteActionMasks(DiscreteActionMasker actionMasker)
         ///
         /// For more information about implementing agent actions see [Agents - Actions].
         ///
-        /// [Agents - Actions]: https://github.com/Unity-Technologies/ml-agents/blob/release_4_docs/docs/Learning-Environment-Design-Agents.md#actions
+        /// [Agents - Actions]: https://github.com/Unity-Technologies/ml-agents/blob/release_5_docs/docs/Learning-Environment-Design-Agents.md#actions
         /// </remarks>
         /// <param name="vectorAction">
         /// An array containing the action vector. The length of the array is specified

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_4_docs/docs//Learning-Environment-Design-Agents.md#recording-demonstrations
+    /// [Imitation Learning - Recording Demonstrations]: https://github.com/Unity-Technologies/ml-agents/blob/release_5_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/Runtime/DiscreteActionMasker.cs

         ///
         /// See [Agents - Actions] for more information on masking actions.
         ///
-        /// [Agents - Actions]: https://github.com/Unity-Technologies/ml-agents/blob/release_4_docs/docs/Learning-Environment-Design-Agents.md#actions
+        /// [Agents - Actions]: https://github.com/Unity-Technologies/ml-agents/blob/release_5_docs/docs/Learning-Environment-Design-Agents.md#actions
         /// </remarks>
         /// <param name="branch">The branch for which the actions will be masked.</param>
         /// <param name="actionIndices">The indices of the masked actions.</param>

docs/Installation-Anaconda-Windows.md

 the ml-agents Conda environment by typing `activate ml-agents`)_:
 
 ```sh
-git clone --branch release_4 https://github.com/Unity-Technologies/ml-agents.git
+git clone --branch release_5 https://github.com/Unity-Technologies/ml-agents.git
-The `--branch release_4` option will switch to the tag of the latest stable
+The `--branch release_5` option will switch to the tag of the latest stable
 release. Omitting that will get the `master` branch which is potentially
 unstable.
 

docs/Installation.md

 of our tutorials / guides assume you have access to our example environments).
 
 ```sh
-git clone --branch release_4 https://github.com/Unity-Technologies/ml-agents.git
+git clone --branch release_5 https://github.com/Unity-Technologies/ml-agents.git
-The `--branch release_4` option will switch to the tag of the latest stable
+The `--branch release_5` option will switch to the tag of the latest stable
 release. Omitting that will get the `master` branch which is potentially
 unstable.
 
 ML-Agents Toolkit for your purposes. If you plan to contribute those changes
-back, make sure to clone the `master` branch (by omitting `--branch release_4`
+back, make sure to clone the `master` branch (by omitting `--branch release_5`
 from the command above). See our
 [Contributions Guidelines](../com.unity.ml-agents/CONTRIBUTING.md) for more
 information on contributing to the ML-Agents Toolkit.

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

 2. Clone the ML-Agents repo and install the required Python packages
 
    ```sh
-   git clone --branch release_4 https://github.com/Unity-Technologies/ml-agents.git
+   git clone --branch release_5 https://github.com/Unity-Technologies/ml-agents.git
    cd ml-agents/ml-agents/
    pip3 install -e .
    ```

gym-unity/gym_unity/__init__.py

 # Version of the library that will be used to upload to pypi
-__version__ = "0.18.0"
+__version__ = "0.18.1"
-__release_tag__ = "release_4"
+__release_tag__ = "release_5"

ml-agents-envs/mlagents_envs/__init__.py

 # Version of the library that will be used to upload to pypi
-__version__ = "0.18.0"
+__version__ = "0.18.1"
-__release_tag__ = "release_4"
+__release_tag__ = "release_5"

ml-agents/mlagents/trainers/__init__.py

 # Version of the library that will be used to upload to pypi
-__version__ = "0.18.0"
+__version__ = "0.18.1"
-__release_tag__ = "release_4"
+__release_tag__ = "release_5"

utils/make_readme_table.py

     ReleaseInfo("release_2", "1.0.2", "0.16.1", "May 20, 2020"),
     ReleaseInfo("release_3", "1.1.0", "0.17.0", "June 10, 2020"),
     ReleaseInfo("release_4", "1.2.0", "0.18.0", "July 15, 2020"),
+    ReleaseInfo("release_5", "1.2.1", "0.18.1", "July 31, 2020"),
 ]
 
 MAX_DAYS = 150  # do not print releases older than this many days