Interactive maze game with neural network AI that learns to navigate labyrinths. Experience machine learning in action through gameplay!

• Intelligent Navigation:
  • 🤖 Neural network-controlled character
  • 🧠 Real-time decision visualization
  • 🔄 On-demand training mode
• Dynamic Environments:
  • 🌀 Procedurally generated mazes
  • 🎚️ Adjustable complexity levels
• Game Modes:
  • 👨‍💻 Manual player control
  • 🤖 AI autonomous navigation
  • 🏁 Progress tracking with scoring
• Immersive Experience: 🔊 Sound effects 🎨 Vector-based graphics 📊 Performance metrics

• Machine Learning:
• Game Engine:
• Data Processing:

1. Clone repository

   git clone https://github.com/Zebaro24-Stud/Neural-Network-Labyrinth.git
   cd Neural-Network-Labyrinth

2. Create virtual environment

   python -m venv venv
   # Windows
   venv\Scripts\activate
   # Linux/Mac
   source venv/bin/activate

3. Install dependencies

   pip install -r requirements.txt

python main.py

• Arrow Keys: Move character (Up, Down, Left, Right)

graph LR
    A[Input Layer<br>4 directions] --> B[Hidden Layer<br>64 neurons]
    B --> C[Output Layer<br>4 actions]
    style A fill:#4CAF50,stroke:#388E3C
    style B fill:#2196F3,stroke:#1976D2
    style C fill:#FF9800,stroke:#F57C00

• Optimizer: Adam
• Loss Function: Categorical Crossentropy
• Activation: ReLU (Hidden), Softmax (Output)

main.py           # Game entry point
GUI2D.py          # Graphical interface
LabyrinthLogic.py # Maze generation & logic
NeuralNetwork.py  # AI implementation
VectorGraphics.py # UI components
config.py         # Game settings
sound/            # Audio assets
requirements.txt  # Dependencies

Manual Mode	AI Mode