🐍 SnakeAI

A classic Snake game powered by the A* pathfinding algorithm that autonomously navigates the snake to food while avoiding collisions.

🎮 Play Live Demo

Why This Project Exists

This project was built to demonstrate practical implementation of the A* pathfinding algorithm in a real-time game environment. It bridges the gap between theoretical algorithm knowledge and applied game development, showcasing how classic AI techniques can solve dynamic pathfinding problems.

Tech Stack

• JavaScript (ES6+) - Core game logic and A* implementation with class-based architecture
• HTML5 Canvas - Rendering engine for the game board
• CSS3 - Responsive styling and layout
• Jest - Testing framework for unit tests
• No Runtime Dependencies - Pure vanilla JavaScript implementation

How to Run

Since this is a browser-based game with no build step required:

Option 1: Open Directly

Simply open index.html in any modern web browser.

# On macOS
open index.html

# On Linux
xdg-open index.html

Option 2: Local Server (Recommended)

# Using Python 3
python -m http.server 8000

# Using Node.js
npx serve .

Then visit http://localhost:8000

Controls

Key	Action
H	Hold to speed up
G	Hold for maximum speed
K	Pause/Resume game
J (while paused)	Step forward one frame

Project Structure

SnakeAI/
├── index.html          # Main HTML entry point with Open Graph meta tags
├── game.js             # Game engine: SnakeGame class with rendering, input, game loop
├── aStar.js            # A* pathfinding algorithm with priority queue
├── package.json        # NPM configuration with Jest testing
├── .babelrc            # Babel configuration for ES6+ transpilation
├── .github/
│   └── workflows/
│       └── ci.yml      # GitHub Actions CI workflow
├── tests/
│   ├── game.test.js    # Unit tests for SnakeGame class
│   └── aStar.test.js   # Unit tests for A* algorithm
├── assets/             # Favicons and icons
│   ├── favicon.ico
│   ├── apple-touch-icon.png
│   └── ...
├── README.md           # Project documentation
└── LICENSE             # MIT License

Testing

This project includes a comprehensive test suite using Jest.

# Install dependencies
npm install

# Run tests
npm test

# Run tests in watch mode
npm run test:watch

# Run tests with coverage
npm run test:coverage

Key Learnings

• A Pathfinding Implementation*: Implemented true A* algorithm with open/closed sets and priority queue, calculating f(n) = g(n) + h(n) where g(n) is the cost from start and h(n) is the Manhattan distance heuristic to the goal. Includes fallback to safe moves when no optimal path exists.

• Real-time Game Loop Management: Learned to manage game state updates, collision detection, and smooth rendering using requestAnimationFrame and interval-based updates.

• Collision Detection & Edge Cases: Implemented boundary checking, self-collision detection, and neighbor validation to prevent the snake from making invalid moves or reversing into itself.

• Class-based Architecture: Refactored from procedural code to ES6 classes (SnakeGame, AStar, PriorityQueue) for better encapsulation, maintainability, and testability.

• Input Validation: Added null checks for DOM elements and validation for user inputs to ensure robust error handling.

License

This project is licensed under the MIT License - see the LICENSE file for details.

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