Understanding AlphaZero Neural Network's SuperHuman Chess Ability
Descrição
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
Artificial Intelligence Is Coming for Our Proteins Office for Science and Society - McGill University
Mastering the game of Go with deep neural networks and tree search
Acquisition of Chess Knowledge in AlphaZero – arXiv Vanity
Google AlphaZero Beats The Best Chess-Playing Software Program
Chess engine sacrifices mastery to mimic human play
How AlphaZero Learns Chess
Alpha Zero's “Alien” Chess Shows the Power, and the Peculiarity, of AI
DeepMind, Google Brain & World Chess Champion Explore How AlphaZero Learns Chess Knowledge, by Synced, SyncedReview
Frontiers AlphaZe∗∗: AlphaZero-like baselines for imperfect information games are surprisingly strong
Checkmate: how we mastered the AlphaZero cover, Science
Self-play reinforcement learning in AlphaGo Zero a, The program plays a
de
por adulto (o preço varia de acordo com o tamanho do grupo)
