Yamagami Tomoki, Segawa Etsuo, Mihana Takatomo, Röhm André, Horisaki Ryoichi, Naruse Makoto
Department of Information Physics and Computing, Graduate School of Information Science and Technology, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo 113-8656, Japan.
Graduate School of Environment and Information Sciences, Yokohama National University, 79-1 Tokiwadai, Hodogaya, Yokohama 240-8501, Kanagawa, Japan.
Entropy (Basel). 2023 May 25;25(6):843. doi: 10.3390/e25060843.
Quantum walks (QWs) have a property that classical random walks (RWs) do not possess-the coexistence of linear spreading and localization-and this property is utilized to implement various kinds of applications. This paper proposes RW- and QW-based algorithms for multi-armed-bandit (MAB) problems. We show that, under some settings, the QW-based model realizes higher performance than the corresponding RW-based one by associating the two operations that make MAB problems difficult-exploration and exploitation-with these two behaviors of QWs.
量子游走（QWs）具有一种经典随机游走（RWs）所不具备的特性——线性扩散与局域化的共存——并且这种特性被用于实现各种应用。本文针对多臂老虎机（MAB）问题提出了基于RW和QW的算法。我们表明，在某些设置下，基于QW的模型通过将使MAB问题变得困难的两种操作——探索和利用——与QW的这两种行为相关联，从而实现了比相应的基于RW的模型更高的性能。
