ML Agents Push Block

Play a Unity-based block pushing game

What is ML Agents Push Block ?

ML Agents Push Block is a Unity-based interactive environment designed for testing and training AI agents. It allows users to engage with a simple yet effective block-pushing game where AI agents can be trained to perform specific tasks. The environment leverages Unity's ML-Agents framework to enable machine learning applications, making it an excellent tool for exploring AI behavior and training models.

Features

โ€ข Unity-Based: Built on the Unity game engine, ensuring high-quality visuals and physics simulation.
โ€ข ML-Agent Integration: Compatible with Unity's ML-Agents framework for training AI models.
โ€ข Sandbox Environment: Provides a controlled space for testing AI behaviors and interactions.
โ€ข Customizable Scenarios: Users can modify the environment to create diverse training conditions.
โ€ข Training and Evaluation Modes: Supports both training and evaluation of AI agents in real-time.
โ€ข Physics-Based Interaction: The block-pushing mechanics are driven by realistic physics for authentic interactions.

How to use ML Agents Push Block ?

  1. Install Unity and ML-Agents: Ensure you have Unity Hub and the ML-Agents package installed on your system.
  2. Launch the Project: Open the ML Agents Push Block project in Unity.
  3. Select Training or Evaluation Mode: Choose between training an AI agent or evaluating a pre-trained model.
  4. Observe AI Behavior: Watch as the AI interacts with the environment and attempts to push the block.
  5. Analyze Results: Use Unity's ML-Agents tools to monitor performance metrics and adjust parameters as needed.
  6. Export the Model: Once satisfied with the AI's performance, export the trained model for use in other projects.

Frequently Asked Questions

What is ML Agents Push Block used for?
ML Agents Push Block is primarily used to train and evaluate AI agents in a block-pushing task, allowing researchers and developers to test and refine machine learning models in a controlled environment.

How do I customize the environment?
You can modify the environment by adjusting Unity scenes, adding obstacles, or changing block properties. This helps in creating diverse training scenarios for your AI agents.

What machine learning algorithms are supported?
ML Agents Push Block supports various algorithms, including Imitation Learning, Reinforcement Learning, and Behavior Cloning, making it versatile for different AI training needs.