Add Match-3 to ToC

Author: maryamziaa

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

@@ -11,5 +11,6 @@ The ML-Agents Toolkit provides several advanced features that extend the core fu
 | [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.                              |
 | [Game Integrations](Integrations.md)                        | Integrate ML-Agents with specific game genres and mechanics (e.g., Match-3). |
+| [Match-3 Integration](Integrations-Match3.md)               | Abstraction and tools for Match-3 board games (board, sensors, actuators).   |
 | [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~/TableOfContents.md

@@ -36,6 +36,7 @@
   * [Inference Engine](Inference-Engine.md)
   * [Hugging Face Integration](Hugging-Face-Integration.md)
   * [Game Integrations](Integrations.md)
+  * [Match-3](Integrations-Match3.md)
   * [ML-Agents Package Settings](Package-Settings.md)
   * [Unity Environment Registry](Unity-Environment-Registry.md)
 * [Cloud & Deployment (deprecated)](Cloud-Deployment.md)

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

@@ -9,18 +9,18 @@ Note that the C# package does not contain the machine learning algorithms for tr
 
 ## Documentation structure
 
-| **Section**                                                           | **Description**                                                                                       |
-|-----------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------|
-| [ML-Agents Theory](ML-Agents-Overview.md)                             | Learn about core concepts of ML-Agents.                                                               |
-| [Get started](Get-Started.md)                                         | Learn how to install ML-Agents and explore samples.                                                   |
-| [Learning Environments and Agents](Learning-Environments-Agents.md)   | Learn about Environments, Agents, creating environments, and using executable builds.                 |
-| [Training](Training.md)                                               | Training workflow, config file, monitoring tools, custom plugins, and profiling.                      |
-| [Python APIs](Python-APIs.md)                                         | Gym, PettingZoo, low-level interfaces, and trainer documentation.                                     |
-| [Python Tutorial with Google Colab](Tutorial-Colab.md)                | Interactive tutorials for using ML-Agents with Google Colab.                                          |
-| [Advanced Features](Advanced-Features.md)                             | Custom sensors, side channels, package settings, environment registry, and input system integrations. |
-| [Cloud & Deployment](Cloud-Deployment.md)                             | Legacy cloud deployment guides (deprecated).                                                          |
-| [Reference & Support](Reference-Support.md)                           | FAQ, troubleshooting, and migration guides.                                                           |
-| [Background](Background.md)                                           | Machine Learning, Unity, PyTorch fundamentals, virtual environments, and ELO rating systems.          |
+| **Section**                                                         | **Description**                                                                                                                                                      |
+|---------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| [ML-Agents Theory](ML-Agents-Overview.md)                           | Learn about core concepts of ML-Agents.                                                                                                                              |
+| [Get started](Get-Started.md)                                       | Learn how to install ML-Agents and explore samples.                                                                                                                  |
+| [Learning Environments and Agents](Learning-Environments-Agents.md) | Learn about Environments, Agents, creating environments, and using executable builds.                                                                                |
+| [Training](Training.md)                                             | Training workflow, config file, monitoring tools, custom plugins, and profiling.                                                                                     |
+| [Python APIs](Python-APIs.md)                                       | Gym, PettingZoo, low-level interfaces, and trainer documentation.                                                                                                    |
+| [Python Tutorial with Google Colab](Tutorial-Colab.md)              | Interactive tutorials for using ML-Agents with Google Colab.                                                                                                         |
+| [Advanced Features](Advanced-Features.md)                           | Custom sensors, side channels, package settings, environment registry, input system integrations, and game integrations (e.g., [Match-3](Integrations-Match3.md)).   |
+| [Cloud & Deployment](Cloud-Deployment.md)                           | Legacy cloud deployment guides (deprecated).                                                                                                                         |
+| [Reference & Support](Reference-Support.md)                         | FAQ, troubleshooting, and migration guides.                                                                                                                          |
+| [Background](Background.md)                                         | Machine Learning, Unity, PyTorch fundamentals, virtual environments, and ELO rating systems.                                                                         |
 
 ## Capabilities
 The package allows you to convert any Unity scene into a learning environment and train character behaviors using a variety of machine-learning algorithms. Additionally, it allows you to embed these trained behaviors back into Unity scenes to control your characters. More specifically, the package provides the following core functionalities: