Genetic Algorithm for Passcode Guessing

This project implements a Genetic Algorithm in JavaScript to efficiently discover a 32-bit binary passcode using natural selection techniques such as selection, crossover, and mutation. It features real-time visualization of convergence rates, customizable parameters, and performance tracking, highlighting the power of evolutionary algorithms in solving optimization problems.

Features

• Customizable Parameters: Adjust population size, mutation rate, and crossover rate.
• Visualization: Dynamic convergence chart to monitor fitness improvements over generations.
• Performance Metrics: Tracks runtime and generations to achieve the target passcode.
• JavaScript Implementation: Lightweight and browser-friendly solution.

Technologies Used

• JavaScript: For the Genetic Algorithm logic.
• Chart.js: For data visualization.
• HTML/CSS: For the user interface.

This project demonstrates the efficiency and flexibility of Genetic Algorithms and provides a foundation for exploring advanced optimization techniques in AI and computational problem-solving.