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An educational maze game that fuses classic arcade action with alphabet learning and adaptive AI.

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Alpha 26 🎮🔤

Play Now GitHub license GitHub stars GitHub issues

An educational arcade maze game that teaches alphabet recognition through classic Pac-Man style gameplay with evolving monsters, power-ups, and procedural daily challenges.

AlphaRun Demo

✨ Features

  • 26 Unique Stages — Collect and deliver letters A → Z across 6 handcrafted maze layouts
  • Smart Monster AI — 4 distinct behaviors: Chaser, Interceptor, Surrounder, and Ambusher
  • Daily Challenge — A new procedurally generated maze every day, seeded by the date
  • Adaptive Difficulty — DDA (Dynamic Difficulty Adjustment) based on your lives and speed
  • Touch, Keyboard & Gamepad Support — Swipe, on-screen D-pad, or WASD/Arrow keys
  • Dark/Light Themes — Toggle between neon arcade and clean light mode
  • AND Many More...!

🚀 Live Demo

➡️ Play Alpha 26 Right Now

No installation required. Works on mobile, tablet, and desktop.

🏗️ Tech Stack

  • Vanilla JavaScript — No frameworks, no build step required
  • HTML5 Canvas 2D — Hardware-accelerated rendering
  • Web Audio API — Procedural sound effects (no external assets)
  • CSS3 Custom Properties — Dynamic theming engine
  • LocalStorage API — Save states, settings, and high scores
  • A Pathfinding* — Real-time monster navigation
  • Mulberry32 PRNG — Deterministic daily challenge generation

🛠️ Local Development

Because the game is a single self-contained HTML file, you don't need a build system. Just serve it:

# Clone the repo
git clone https://github.com/ethioel/AlphaRun-HTML.git
cd AlphaRun-HTML

# Option 1: Python simple server
python -m http.server 8000

# Option 2: Node.js (if you have npx)
npx serve .

# Option 3: VS Code Live Server extension
# Just right-click index.html → "Open with Live Server"

Then open http://localhost:8000 in your browser.

🚢 Deployment

This repo includes a GitHub Actions workflow (.github/workflows/deploy.yml) that automatically deploys the main branch to GitHub Pages on every push.

🧠 Game Design Notes

Monster AI Roles

Role Behavior
Chaser (Pink) Direct A* path to player
Interceptor (Yellow) Predicts player movement 4 tiles ahead
Surrounder (Cyan) Flanks from calculated angles
Ambusher (Red) Camps the delivery target

Dynamic Difficulty Adjustment (DDA)

  • Low Lives (1) → Player speed +10%, chase cooldown +5s
  • High Lives + Fast Time → Monster speed slightly increased, chase cooldown -5s
  • Stage Progression → Monster count increases every 4 stages (cap: 7)

Daily Challenge Algorithm

seed = year * 10000 + month * 100 + day
maze = procedural(seed)

Uses Mulberry32 PRNG for deterministic, cross-platform daily mazes.

🤝 Contributing

We welcome contributions! Please read CONTRIBUTING.md for details on our code of conduct and the process for submitting pull requests.

📝 License

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

🙏 Acknowledgments

  • Inspired by classic arcade maze games
  • Built for educational purposes to help kids learn alphabet recognition
  • Font: System UI / Apple Color Emoji for native emoji rendering

Made with ❤️ by Samuel.K
📧 Contact • 🐛 Report Bug • 💡 Request Feature

About

An educational maze game that fuses classic arcade action with alphabet learning and adaptive AI.

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