Understanding AlphaZero Neural Network's SuperHuman Chess Ability
Por um escritor misterioso
Last updated 21 setembro 2024
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
DeepMind's AlphaZero beats state-of-the-art chess and shogi game engines
AlphaZero algorithm can pick up victory moves in chess
Neural Networks - Chessprogramming wiki
To err is not just human: U of T researchers develop AI that plays chess like a person
Google's self-learning AI AlphaZero masters chess in 4 hours
CB article on AlphaZero suggests AlphaZero is playing a different kind of chess. : r/chess
Alpha Zero's “Alien” Chess Shows the Power, and the Peculiarity, of AI
What does Alpha Zero's win over Stockfish mean for chess? - Quora
Acquisition of Chess Knowledge in AlphaZero
Understanding AlphaZero Neural Network's SuperHuman Chess Ability - MarkTechPost
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