14 citations · 42 across the 21 of their papers we have counts for
5 papers · 1 filter
Quantum spatial best-arm identification via quantum walks
Tomoki Yamagami, Etsuo Segawa, Takatomo Mihana +3
Quantum reinforcement learning has emerged as a framework combining quantum computation with sequential decision-making, and applications to the multi-armed bandit (MAB) problem ha…
Multi-player conflict avoidance through entangled quantum walks
Honoka Shiratori, Tomoki Yamagami, Etsuo Segawa +3
Quantum computing has the potential to solve complex problems faster and more efficiently than classical computing. It can achieve speedups by leveraging quantum phenomena like sup…
Scalable Conflict-free Decision Making with Photons
Kohei Konaka, André Röhm, Takatomo Mihana +1
Quantum optics utilizes the unique properties of light for computation or communication. In this work, we explore its ability to solve certain reinforcement learning tasks, with a…
Bandit Algorithm Driven by a Classical Random Walk and a Quantum Walk
Tomoki Yamagami, Etsuo Segawa, Takatomo Mihana +3
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 imp…
Conflict-free joint sampling for preference satisfaction through quantum interference
Hiroaki Shinkawa, Nicolas Chauvet, André Röhm +4
Collective decision-making is vital for recent information and communications technologies. In our previous research, we mathematically derived conflict-free joint decision-making…