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Materials design and discovery can be represented as selecting the optimal structure from a space of candidates that optimizes a target property. Since the number of candidates can be exponentially proportional to the structure determination variables, the optimal structure must be obtained efficiently. Recently, inspired by its success in the Go computer game, several approaches have applied Monte Carlo tree search (MCTS) to solve optimization problems in natural sciences including materials science. In this paper, we briefly reviewed applications of MCTS in materials design and

権利情報:

キーワード: Materials design and discovery

刊行年月日: 2019-06-20

出版者: Cambridge University Press

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研究助成金:

原稿種別: 査読前原稿 (Author's original)

MDR DOI:

公開URL: https://doi.org/10.1557/mrc.2019.40

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更新時刻: 2024-01-05 22:11:17 +0900

MDRでの公開時刻: 2021-08-14 03:55:56 +0900