AlphaZero Chess: How It Works, What Sets It Apart, and What It Can Tell Us

To those of you who have an interest in chess or who have been monitoring recent developments in artificial intelligence the name "AlphaZero" will be instantly recognisable; its victory over the then-leading chess engine in the world, Stockfish, had revolutionised the way that chess is played by both computers and, indeed, humans. However, if you aren't a chess aficionado or have missed the news a couple of years ago, you might be wondering what exactly this AlphaZero really is, and what makes it worth writing an entire blog post about. For you, I will explain. In short, AlphaZero is a game-playing program that, through a combination of self-play and neural network reinforcement learning (more on that later), is able to learn to play games such as chess and Go from scratch that is, after being fed nothing more than the rules of said games. In fact, a newer derivative of AlphaZero, called MuZero, isn't limited to only board games such as chess, but can also learn to play a range of simple video games from the Atari collection.