WorldsHardestGameAI

This repository contains the AI pathfinding implementation for the "World's Hardest Game" developed as a project for the Artificial Intelligence (AI) class during my Bachelor's degree at King Mongkut's University of Technology North Bangkok (KMUTNB).

Project Overview

The "World's Hardest Game" is a notoriously challenging browser game that requires precise navigation through a maze-like environment. This project focuses on implementing AI algorithms to autonomously solve the game.

Key Features

• Pathfinding Algorithms:
  • Implemented various pathfinding algorithms, such as A* search, to find optimal or near-optimal paths.
  • Explored and compared the performance of different algorithms in the context of the game's complex environment.
• Game State Representation:
  • Developed a representation of the game state that allows the AI to effectively reason about the environment.
  • Implemented methods to extract relevant information from the game, such as player position, obstacles, and goal locations.
• AI Agent Control:
  • Created an AI agent that can interact with the game, control the player character, and execute the calculated paths.
• Educational Purpose:
  • This project was primarily developed for educational purposes, demonstrating the practical application of AI pathfinding techniques.

Getting Started

1. Clone the Repository:

   git clone [repository URL]
   cd WorldsHardestGameAI

2. Dependencies:

   • Install any required libraries or dependencies (e.g., Python libraries for AI algorithms, browser automation tools if used). Refer to the project's documentation or requirements file.

3. Running the AI Agent:

   • Follow the instructions in the project's documentation to run the AI agent. This may involve running a Python script or executing a browser extension.

4. Configuration

   • If the code needs any configuration, such as file paths, or game specific settings, modify the config files or variables within the code.

Contents

• AI Algorithms:
  • Implementation of pathfinding algorithms (e.g., A*).
  • Code for game state representation and manipulation.
• Game Interface:
  • Code for interacting with the "World's Hardest Game" (e.g., browser automation, game state extraction).
• Project Documentation:
  • Reports, presentations, or other documentation related to the project.

Acknowledgments

• KMUTNB for providing the opportunity to learn and apply AI concepts.
• The creators of the "World's Hardest Game"

Note

This project was developed as part of an academic course and may not be suitable for production use without further development and optimization.