AlphaZero的悖论:策略性vs.最优玩法

2020 IEEE 39th International Performance Computing and Communications Conference (IPCCC) Pub Date : 2020-11-06 DOI:10.1109/IPCCC50635.2020.9391562

Ze-Li Dou, Liran Ma, Khiem Nguyen, Kien X. Nguyen

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引用次数: 0

摘要

本文从7×7棋盘的局部和全局最优棋局的角度定量地分析了alphazero型算法。通过对人工智能代理的有针对性的评估，作者揭示了这种算法的策略，即胜率主导的本质，从而揭示了某些针对最优玩法的固有障碍。然后探索可能的补救措施，导致技术可能有助于进一步定量分析这些算法和寻找最佳解决方案，在7×7和更大的板。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Paradox of AlphaZero: Strategic vs. Optimal Plays

This article analyzes AlphaZero-type algorithms quantitatively from the viewpoint of local and global optimal sequences of play on a 7×7 board. Through targeted evaluation of the AI agent, the authors reveal the strategic, that is, winrate-dominated, nature of such algorithms, and expose thereby certain inherent obstacles against optimal play. Possible remedies are then explored, leading to techniques that may help further quantitative analysis of those algorithms and for the search for optimal solutions, on 7×7 as well as larger boards.

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2020 IEEE 39th International Performance Computing and Communications Conference (IPCCC)

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