Quantum walks (QWs) have the property that classical random walks (RWs) do not possess -- coexistence of linear spreading and localization -- and this property is utilized to implement various kinds of applications. This paper proposes a quantum-walk-based algorithm for multi-armed-bandit (MAB) problems by associating the two operations that make MAB problems difficult -- exploration and exploitation -- with these two behaviors of QWs. We show that this new policy based on the QWs realizes high performance compared with the corresponding RW-based one.
翻译:量子游走(QWs)拥有经典随机游走(RWs)所不具备的性质--线性扩散和局部化的共存--并且这种性质被用于实现各种应用程序。本文提出了一种基于量子游走算法的多臂强盗(MAB)问题算法,将使MAB问题难以解决的两个操作 - 探索和利用 - 与量子游走的这两种行为相关联。我们表明这种新的QWs策略相比相应的RWs策略实现了高性能。