![]() We also provide aīehavioural analysis focusing on opening play, including qualitative analysisįrom chess Grandmaster Vladimir Kramnik. Probing for a broad range of human chess concepts we show when and where theseĬoncepts are represented in the AlphaZero network. In this work we provide evidence that human knowledge isĪcquired by the AlphaZero neural network as it trains on the game of chess. ![]() Source: Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm. AlphaZero is a reinforcement learning agent for playing board games such as Go, chess, and shogi. Will be restricted, ultimately limiting what we can achieve with neural network in Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm. Representations of strong neural networks bear no resemblance to humanĬoncepts, our ability to understand faithful explanations of their decisions ![]() This question is of both scientific and practical interest. Authors: Thomas McGrath, Andrei Kapishnikov, Nenad Tomašev, Adam Pearce, Demis Hassabis, Been Kim, Ulrich Paquet, Vladimir Kramnik Download PDF Abstract: What is learned by sophisticated neural network agents such as AlphaZero?
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