3 citations · 6 across the 16 of their papers we have counts for
5 papers · 1 filter
Parallel photonic accelerator for decision making using optical spatiotemporal chaos
Kensei Morijiri, Kento Takehana, Takatomo Mihana +3
Photonic accelerators have attracted increasing attention in artificial intelligence applications. The multi-armed bandit problem is a fundamental problem of decision making using…
Parallel bandit architecture based on laser chaos for reinforcement learning
Takashi Urushibara, Nicolas Chauvet, Satoshi Kochi +5
Accelerating artificial intelligence by photonics is an active field of study aiming to exploit the unique properties of photons. Reinforcement learning is an important branch of m…
Adaptive model selection in photonic reservoir computing by reinforcement learning
Kazutaka Kanno, Makoto Naruse, Atsushi Uchida
Photonic reservoir computing is an emergent technology toward beyond-Neumann computing. Although photonic reservoir computing provides superior performance in environments whose ch…
Scalable photonic reinforcement learning by time-division multiplexing of laser chaos
Makoto Naruse, Takatomo Mihana, Hirokazu Hori +4
Reinforcement learning involves decision making in dynamic and uncertain environments and constitutes a crucial element of artificial intelligence. In our previous work, we experim…
Nanoscale photonic network for solution searching and decision making problems
Makoto Naruse, Masashi Aono, Song-Ju Kim
Nature-inspired devices and architectures are attracting considerable attention for various purposes, including the development of novel computing techniques based on spatiotempora…