Update more docs

Author: maryamziaa

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

@@ -9,10 +9,12 @@ These advanced features are particularly useful when:
 - You're deploying trained models in production environments
 - You want to leverage pre-trained models from the Hugging Face ecosystem
 
-| **Feature**                                                   | **Description**                                           |
-|---------------------------------------------------------------|-----------------------------------------------------------|
+| **Feature**                                                  | **Description**                                          |
+|--------------------------------------------------------------|----------------------------------------------------------|
 | [Custom Side Channels](Custom-SideChannels.md)               | Create custom communication channels between Unity and Python. |
-| [Custom Grid Sensors](Custom-GridSensors.md)                 | Build specialized grid-based sensors for spatial data.   |
-| [Input System Integration](InputSystem-Integration.md)       | Integrate ML-Agents with Unity's Input System.           |
-| [Inference Engine](Inference-Engine.md)                      | Deploy trained models for real-time inference.           |
-| [Hugging Face Integration](Hugging-Face-Integration.md)      | Connect with Hugging Face models and ecosystem.          |
+| [Custom Grid Sensors](Custom-GridSensors.md)                 | Build specialized grid-based sensors for spatial data.  |
+| [Input System Integration](InputSystem-Integration.md)       | Integrate ML-Agents with Unity's Input System.          |
+| [Inference Engine](Inference-Engine.md)                      | Deploy trained models for real-time inference.          |
+| [Hugging Face Integration](Hugging-Face-Integration.md)      | Connect with Hugging Face models and ecosystem.         |
+| [ML-Agents Package Settings](Package-Settings.md)            | Configure advanced package settings and preferences.     |
+| [Unity Environment Registry](Unity-Environment-Registry.md)  | Manage and register Unity environments programmatically. |

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

@@ -7,3 +7,5 @@ This section provides foundational knowledge to help you understand the technolo
 | [Machine Learning](Background-Machine-Learning.md) | Introduction to ML concepts, reinforcement learning, and training principles. |
 | [Unity](Background-Unity.md)                       | Unity fundamentals for ML-Agents development and environment creation.        |
 | [PyTorch](Background-PyTorch.md)                   | PyTorch basics for understanding the training pipeline and neural networks.   |
+| [Using Virtual Environment](Using-Virtual-Environment.md) | Setting up and managing Python virtual environments for ML-Agents.     |
+| [ELO Rating System](ELO-Rating-System.md)          | Understanding ELO rating system for multi-agent training evaluation.         |

com.unity.ml-agents/Documentation~/Learning-Environment-Executable.md

@@ -194,5 +194,5 @@ graphics display in the Unity executable. There are two ways to achieve this:
 
 If you want to train with graphics (for example, using camera and visual observations), you'll
 need to set up display rendering support (e.g. xvfb) on you server machine. In our
-[Colab Notebook Tutorials](ML-Agents-Toolkit-Documentation.md#python-tutorial-with-google-colab), the Setup section has
+[Colab Notebook Tutorials](Tutorial-Colab.md), the Setup section has
 examples of setting up xvfb on servers.

com.unity.ml-agents/Documentation~/Learning-Environments-Agents.md

@@ -6,3 +6,4 @@ Use the following topics to dive into designing Learning Environments and Agents
 | [Designing Learning Environments](Learning-Environment-Design.md)               | Learn how to structure and configure environments               |
 | [Designing Agents](Learning-Environment-Design-Agents.md)                       | Understand how to create agents                                 |
 | [Sample: Making a New Learning Environment](Learning-Environment-Create-New.md) | Follow a step-by-step example to build a learning environment.  |
+| [Using an Executable Environment](Learning-Environment-Executable.md)          | Deploy and use executable environments for training.            |

com.unity.ml-agents/Documentation~/ML-Agents-Toolkit-Documentation.md

@@ -3,8 +3,10 @@
 The Python APIs allow you to control and interact with Unity environments from Python scripts. Each API is designed for specific use cases and offers different levels of abstraction and functionality.
 
 
-| **API**                                           | **Description**                                                    |
-|---------------------------------------------------|--------------------------------------------------------------------|
-| [Python Gym API](Python-Gym-API.md)              | OpenAI Gym-compatible interface for standard RL workflows.        |
-| [Python PettingZoo API](Python-PettingZoo-API.md)| Multi-agent environment interface compatible with PettingZoo.     |
-| [Python Low-Level API](Python-LLAPI.md)          | Direct low-level access for custom training and advanced use cases.|
+| **API**                                                                              | **Description**                                                     |
+|--------------------------------------------------------------------------------------|---------------------------------------------------------------------|
+| [Python Gym API](Python-Gym-API.md)                                                  | OpenAI Gym-compatible interface for standard RL workflows.          |
+| [Python PettingZoo API](Python-PettingZoo-API.md)                                    | Multi-agent environment interface compatible with PettingZoo.       |
+| [Python Low-Level API](Python-LLAPI.md)                                              | Direct low-level access for custom training and advanced use cases. |
+| [Python Low-Level API Documentation](Python-LLAPI-Documentation.md)                  | Detailed documentation for the Python Low-Level API.                |
+| [On/Off Policy Trainer Documentation](Python-On-Off-Policy-Trainer-Documentation.md) | Documentation for on-policy and off-policy training methods.        |

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

@@ -1,111 +1,4 @@
-# Table of Contents
-
-* [mlagents\_envs.base\_env](#mlagents_envs.base_env)
-  * [DecisionStep](#mlagents_envs.base_env.DecisionStep)
-  * [DecisionSteps](#mlagents_envs.base_env.DecisionSteps)
-    * [agent\_id\_to\_index](#mlagents_envs.base_env.DecisionSteps.agent_id_to_index)
-    * [\_\_getitem\_\_](#mlagents_envs.base_env.DecisionSteps.__getitem__)
-    * [empty](#mlagents_envs.base_env.DecisionSteps.empty)
-  * [TerminalStep](#mlagents_envs.base_env.TerminalStep)
-  * [TerminalSteps](#mlagents_envs.base_env.TerminalSteps)
-    * [agent\_id\_to\_index](#mlagents_envs.base_env.TerminalSteps.agent_id_to_index)
-    * [\_\_getitem\_\_](#mlagents_envs.base_env.TerminalSteps.__getitem__)
-    * [empty](#mlagents_envs.base_env.TerminalSteps.empty)
-  * [ActionTuple](#mlagents_envs.base_env.ActionTuple)
-    * [discrete\_dtype](#mlagents_envs.base_env.ActionTuple.discrete_dtype)
-  * [ActionSpec](#mlagents_envs.base_env.ActionSpec)
-    * [is\_discrete](#mlagents_envs.base_env.ActionSpec.is_discrete)
-    * [is\_continuous](#mlagents_envs.base_env.ActionSpec.is_continuous)
-    * [discrete\_size](#mlagents_envs.base_env.ActionSpec.discrete_size)
-    * [empty\_action](#mlagents_envs.base_env.ActionSpec.empty_action)
-    * [random\_action](#mlagents_envs.base_env.ActionSpec.random_action)
-    * [create\_continuous](#mlagents_envs.base_env.ActionSpec.create_continuous)
-    * [create\_discrete](#mlagents_envs.base_env.ActionSpec.create_discrete)
-    * [create\_hybrid](#mlagents_envs.base_env.ActionSpec.create_hybrid)
-  * [DimensionProperty](#mlagents_envs.base_env.DimensionProperty)
-    * [UNSPECIFIED](#mlagents_envs.base_env.DimensionProperty.UNSPECIFIED)
-    * [NONE](#mlagents_envs.base_env.DimensionProperty.NONE)
-    * [TRANSLATIONAL\_EQUIVARIANCE](#mlagents_envs.base_env.DimensionProperty.TRANSLATIONAL_EQUIVARIANCE)
-    * [VARIABLE\_SIZE](#mlagents_envs.base_env.DimensionProperty.VARIABLE_SIZE)
-  * [ObservationType](#mlagents_envs.base_env.ObservationType)
-    * [DEFAULT](#mlagents_envs.base_env.ObservationType.DEFAULT)
-    * [GOAL\_SIGNAL](#mlagents_envs.base_env.ObservationType.GOAL_SIGNAL)
-  * [ObservationSpec](#mlagents_envs.base_env.ObservationSpec)
-  * [BehaviorSpec](#mlagents_envs.base_env.BehaviorSpec)
-  * [BaseEnv](#mlagents_envs.base_env.BaseEnv)
-    * [step](#mlagents_envs.base_env.BaseEnv.step)
-    * [reset](#mlagents_envs.base_env.BaseEnv.reset)
-    * [close](#mlagents_envs.base_env.BaseEnv.close)
-    * [behavior\_specs](#mlagents_envs.base_env.BaseEnv.behavior_specs)
-    * [set\_actions](#mlagents_envs.base_env.BaseEnv.set_actions)
-    * [set\_action\_for\_agent](#mlagents_envs.base_env.BaseEnv.set_action_for_agent)
-    * [get\_steps](#mlagents_envs.base_env.BaseEnv.get_steps)
-* [mlagents\_envs.environment](#mlagents_envs.environment)
-  * [UnityEnvironment](#mlagents_envs.environment.UnityEnvironment)
-    * [\_\_init\_\_](#mlagents_envs.environment.UnityEnvironment.__init__)
-    * [close](#mlagents_envs.environment.UnityEnvironment.close)
-* [mlagents\_envs.registry](#mlagents_envs.registry)
-* [mlagents\_envs.registry.unity\_env\_registry](#mlagents_envs.registry.unity_env_registry)
-  * [UnityEnvRegistry](#mlagents_envs.registry.unity_env_registry.UnityEnvRegistry)
-    * [register](#mlagents_envs.registry.unity_env_registry.UnityEnvRegistry.register)
-    * [register\_from\_yaml](#mlagents_envs.registry.unity_env_registry.UnityEnvRegistry.register_from_yaml)
-    * [clear](#mlagents_envs.registry.unity_env_registry.UnityEnvRegistry.clear)
-    * [\_\_getitem\_\_](#mlagents_envs.registry.unity_env_registry.UnityEnvRegistry.__getitem__)
-* [mlagents\_envs.side\_channel](#mlagents_envs.side_channel)
-* [mlagents\_envs.side\_channel.raw\_bytes\_channel](#mlagents_envs.side_channel.raw_bytes_channel)
-  * [RawBytesChannel](#mlagents_envs.side_channel.raw_bytes_channel.RawBytesChannel)
-    * [on\_message\_received](#mlagents_envs.side_channel.raw_bytes_channel.RawBytesChannel.on_message_received)
-    * [get\_and\_clear\_received\_messages](#mlagents_envs.side_channel.raw_bytes_channel.RawBytesChannel.get_and_clear_received_messages)
-    * [send\_raw\_data](#mlagents_envs.side_channel.raw_bytes_channel.RawBytesChannel.send_raw_data)
-* [mlagents\_envs.side\_channel.outgoing\_message](#mlagents_envs.side_channel.outgoing_message)
-  * [OutgoingMessage](#mlagents_envs.side_channel.outgoing_message.OutgoingMessage)
-    * [\_\_init\_\_](#mlagents_envs.side_channel.outgoing_message.OutgoingMessage.__init__)
-    * [write\_bool](#mlagents_envs.side_channel.outgoing_message.OutgoingMessage.write_bool)
-    * [write\_int32](#mlagents_envs.side_channel.outgoing_message.OutgoingMessage.write_int32)
-    * [write\_float32](#mlagents_envs.side_channel.outgoing_message.OutgoingMessage.write_float32)
-    * [write\_float32\_list](#mlagents_envs.side_channel.outgoing_message.OutgoingMessage.write_float32_list)
-    * [write\_string](#mlagents_envs.side_channel.outgoing_message.OutgoingMessage.write_string)
-    * [set\_raw\_bytes](#mlagents_envs.side_channel.outgoing_message.OutgoingMessage.set_raw_bytes)
-* [mlagents\_envs.side\_channel.engine\_configuration\_channel](#mlagents_envs.side_channel.engine_configuration_channel)
-  * [EngineConfigurationChannel](#mlagents_envs.side_channel.engine_configuration_channel.EngineConfigurationChannel)
-    * [on\_message\_received](#mlagents_envs.side_channel.engine_configuration_channel.EngineConfigurationChannel.on_message_received)
-    * [set\_configuration\_parameters](#mlagents_envs.side_channel.engine_configuration_channel.EngineConfigurationChannel.set_configuration_parameters)
-    * [set\_configuration](#mlagents_envs.side_channel.engine_configuration_channel.EngineConfigurationChannel.set_configuration)
-* [mlagents\_envs.side\_channel.side\_channel\_manager](#mlagents_envs.side_channel.side_channel_manager)
-  * [SideChannelManager](#mlagents_envs.side_channel.side_channel_manager.SideChannelManager)
-    * [process\_side\_channel\_message](#mlagents_envs.side_channel.side_channel_manager.SideChannelManager.process_side_channel_message)
-    * [generate\_side\_channel\_messages](#mlagents_envs.side_channel.side_channel_manager.SideChannelManager.generate_side_channel_messages)
-* [mlagents\_envs.side\_channel.stats\_side\_channel](#mlagents_envs.side_channel.stats_side_channel)
-  * [StatsSideChannel](#mlagents_envs.side_channel.stats_side_channel.StatsSideChannel)
-    * [on\_message\_received](#mlagents_envs.side_channel.stats_side_channel.StatsSideChannel.on_message_received)
-    * [get\_and\_reset\_stats](#mlagents_envs.side_channel.stats_side_channel.StatsSideChannel.get_and_reset_stats)
-* [mlagents\_envs.side\_channel.incoming\_message](#mlagents_envs.side_channel.incoming_message)
-  * [IncomingMessage](#mlagents_envs.side_channel.incoming_message.IncomingMessage)
-    * [\_\_init\_\_](#mlagents_envs.side_channel.incoming_message.IncomingMessage.__init__)
-    * [read\_bool](#mlagents_envs.side_channel.incoming_message.IncomingMessage.read_bool)
-    * [read\_int32](#mlagents_envs.side_channel.incoming_message.IncomingMessage.read_int32)
-    * [read\_float32](#mlagents_envs.side_channel.incoming_message.IncomingMessage.read_float32)
-    * [read\_float32\_list](#mlagents_envs.side_channel.incoming_message.IncomingMessage.read_float32_list)
-    * [read\_string](#mlagents_envs.side_channel.incoming_message.IncomingMessage.read_string)
-    * [get\_raw\_bytes](#mlagents_envs.side_channel.incoming_message.IncomingMessage.get_raw_bytes)
-* [mlagents\_envs.side\_channel.float\_properties\_channel](#mlagents_envs.side_channel.float_properties_channel)
-  * [FloatPropertiesChannel](#mlagents_envs.side_channel.float_properties_channel.FloatPropertiesChannel)
-    * [on\_message\_received](#mlagents_envs.side_channel.float_properties_channel.FloatPropertiesChannel.on_message_received)
-    * [set\_property](#mlagents_envs.side_channel.float_properties_channel.FloatPropertiesChannel.set_property)
-    * [get\_property](#mlagents_envs.side_channel.float_properties_channel.FloatPropertiesChannel.get_property)
-    * [list\_properties](#mlagents_envs.side_channel.float_properties_channel.FloatPropertiesChannel.list_properties)
-    * [get\_property\_dict\_copy](#mlagents_envs.side_channel.float_properties_channel.FloatPropertiesChannel.get_property_dict_copy)
-* [mlagents\_envs.side\_channel.environment\_parameters\_channel](#mlagents_envs.side_channel.environment_parameters_channel)
-  * [EnvironmentParametersChannel](#mlagents_envs.side_channel.environment_parameters_channel.EnvironmentParametersChannel)
-    * [set\_float\_parameter](#mlagents_envs.side_channel.environment_parameters_channel.EnvironmentParametersChannel.set_float_parameter)
-    * [set\_uniform\_sampler\_parameters](#mlagents_envs.side_channel.environment_parameters_channel.EnvironmentParametersChannel.set_uniform_sampler_parameters)
-    * [set\_gaussian\_sampler\_parameters](#mlagents_envs.side_channel.environment_parameters_channel.EnvironmentParametersChannel.set_gaussian_sampler_parameters)
-    * [set\_multirangeuniform\_sampler\_parameters](#mlagents_envs.side_channel.environment_parameters_channel.EnvironmentParametersChannel.set_multirangeuniform_sampler_parameters)
-* [mlagents\_envs.side\_channel.side\_channel](#mlagents_envs.side_channel.side_channel)
-  * [SideChannel](#mlagents_envs.side_channel.side_channel.SideChannel)
-    * [queue\_message\_to\_send](#mlagents_envs.side_channel.side_channel.SideChannel.queue_message_to_send)
-    * [on\_message\_received](#mlagents_envs.side_channel.side_channel.SideChannel.on_message_received)
-    * [channel\_id](#mlagents_envs.side_channel.side_channel.SideChannel.channel_id)
+# Python Low-Level API Documentation
 
 <a name="mlagents_envs.base_env"></a>
 # mlagents\_envs.base\_env