Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore a comprehensive lecture on artificial intelligence focusing on genetic algorithms applied to Sudoku puzzles. Learn about assignment goals, Sudoku mechanics, user interface design, and key genetic algorithm concepts including fitness functions, population size, mutation rates, and elitism. Dive into the implementation details with explanations of the Sudoku class, GASettings class, and GA_Student class. Understand the GAEvolve function, selection methods like roulette wheel, crossover techniques, and mutation strategies. Gain insights into modifying fitness functions for Sudoku and generating random populations. This lecture, part of the COMP3200 Intro to Artificial Intelligence course at Memorial University, provides a thorough foundation for implementing genetic algorithms to solve complex puzzles.