Understanding AlphaZero Neural Network's SuperHuman Chess Ability

As a common and (sometimes) proven belief, deep learning systems seem to learn uninterpretable representations and are far from human understanding. Recently, some studies have highlighted the fact that this may not always be applicable, and some networks may be able to learn human-readable representations. Unfortunately, this ability could merely come from the fact that these networks are exposed to human-generated data. So, to demonstrate their ability to learn like humans (and not that they are simply memorizing human-created labels), it is necessary to test them without any label.  Following this idea, the DeepMind and Google Brain teams, together with

Neural Networks - Chessprogramming wiki

Understanding AlphaZero Neural Network's SuperHuman Chess Ability - MarkTechPost

AlphaZero Explained · On AI

A Beginner's Guide to Machine Learning - RapidMiner

DeepMind, Google Brain & World Chess Champion Explore How AlphaZero Learns Chess Knowledge

Study of AI projects

AlphaZero and the Losing Future of Human Wisdom

Alphazero :: Computer-bridge1

Frontiers AlphaZe∗∗: AlphaZero-like baselines for imperfect information games are surprisingly strong

AlphaZero - Chessprogramming wiki