In the course of writing my April 2019 review for Chess Life, devoted to the fascinating new Game Changer by Matthew Sadler and Natasha Regan, I had occasion to spend more than a few hours studying Leela Chess Zero, or “Leela.” Like Alpha Zero, Leela is a self-learning algorithm, combining a self-trained neural net and Monte Carlo-style searching to create one of the two or three strongest chess-playing entities on the planet.
But unlike Alpha Zero, Leela is open-source and freely available to use by anyone who downloads it. And with its near-win in the TCEC 14 super-tournament, Leela became a source of intense interest among computer chess aficionados and practical players looking for a new analytical tool. This game, in part, stoked that interest.
There are important differences between self-learning engines like Leela and traditional alpha-beta searchers like Stockfish. Some of these differences are easy to grasp, but others require explanation and instruction. Watching this video, the first in a series of occasional efforts for CLO, will tell you exactly what you need to know to install, configure, and interpret Leela’s output.