  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.
