Understanding AlphaZero Neural Network's SuperHuman Chess Ability
Por um escritor misterioso
Last updated 12 janeiro 2025
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
AlphaZero learns human concepts
Google AlphaZero Beats The Best Chess-Playing Software Program
Acquisition of Chess Knowledge in AlphaZero
AlphaZero AI beats champion chess program after teaching itself in four hours, DeepMind
CB article on AlphaZero suggests AlphaZero is playing a different kind of chess. : r/chess
Understanding AlphaZero Neural Network's SuperHuman Chess Ability - MarkTechPost
Electronics, Free Full-Text
How Google's AI Mastered All Chess Knowledge in Just 4 Hours
Acquisition of chess knowledge in AlphaZero
Reimagining Chess with AlphaZero, February 2022
AlphaZero algorithm can pick up victory moves in chess
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