AIUT-Environments

Create a fully-functional mini-game application using the 'AIUT-Environments' Python package. This game will simulate a simple exploration environment where a player navigates through a grid-based world to collect treasures while avoiding obstacles. The goal is to maximize the collected treasure points while minimizing collision penalties. Here's a detailed breakdown of the project requirements:

1. **Setup**: Install the 'AIUT-Environments' package if it isn't already installed. Ensure you have Python and pip installed on your system.
2. **Environment Creation**: Utilize the 'AIUT-Environments' package to create a custom grid-based environment. This environment should include configurable parameters such as grid size, initial player position, number and type of obstacles, and treasure locations.
3. **Gameplay Mechanics**: Implement basic gameplay mechanics including movement commands (up, down, left, right), collision detection, and treasure collection logic. Each move should be logged with its outcome (e.g., 'Player moved up', 'Player found treasure at (x,y)', 'Player hit obstacle at (x,y)').
4. **Scoring System**: Develop a scoring system that awards points for treasure collection and penalizes for collisions. The score should be displayed after each move and also at the end of the game.
5. **User Interface**: Create a simple command-line interface (CLI) for the game. The CLI should allow players to input their moves and display the current state of the game, including the player's position, remaining treasures, and current score.
6. **Challenge Modes**: Introduce different challenge modes within the game, each with varying levels of difficulty. These could include increased grid sizes, more obstacles, or faster-moving obstacles.
7. **AI Integration (Optional)**: For advanced users, implement a feature that allows the use of a simple AI algorithm (such as Q-learning) to navigate the environment autonomously. This AI should be trained using the 'AIUT-Environments' package's functionalities to learn the optimal path to collect all treasures.
8. **Documentation**: Write clear documentation explaining how to install and run the game, as well as how to modify the game environment parameters. Include examples of how to extend the game with new features.
9. **Testing**: Conduct thorough testing of your game to ensure all functionalities work as expected. Include unit tests for the core game logic and integration tests for the CLI and AI components.
10. **Deployment**: Package your game as a standalone executable or a Docker container for easy deployment on different systems.

This project not only serves as a fun way to explore the capabilities of 'AIUT-Environments' but also provides a practical example of how to integrate game development principles with AI learning environments.