The popular board game of Risk has many fans around the world. Using a Python-based simulation of the game, we use a genetic algorithm to train a risk-playing algorithm.
During this talk we’ll explain what genetic algorithms are and we’ll explain an entertaining use-case: how to win at popular board games. During the talk we’ll demo how object oriented patterns help with the design and implementation of these algorithms. We’ll also demonstrate a library that allows users to push their own risk bots into a game and battle it out on.