Neural-Network-Labyrinth 🧠🔄🎮

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

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✨ Core Features

• 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

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🧰 Tech Stack

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

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⚙️ Installation & Setup

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

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🚀 Launching the Game

python main.py

Controls

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

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🧠 Neural Network Architecture

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

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

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🗂️ Project Structure

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

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🎮 Gameplay Preview

Manual Mode	AI Mode

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📬 Contacts

👨‍💻 Developer	📧 Email	💻 GitHub
Denys Shcherbatyi	zebaro.work@gmail.com	@Zebaro24
Dmitro Itsko	cloud.me.fr@gmail.com	@WhiteDh
Oleksandr Yakovenko	wu662542@gmail.com	@Glek-Stud