17 citations · 65 across the 11 of their papers we have counts for
8 papers
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…
Controlling chaotic itinerancy in laser dynamics for reinforcement learning
Ryugo Iwami, Takatomo Mihana, Kazutaka Kanno +3
Photonic artificial intelligence has attracted considerable interest in accelerating machine learning; however, the unique optical properties have not been fully utilized for achie…
Efficient Pairing in Unknown Environments: Minimal Observations and TSP-based Optimization
Naoki Fujita, Nicolas Chauvet, Andre Roehm +4
Generating paired sequences with maximal compatibility from a given set is one of the most important challenges in various applications, including information and communication tec…
Single photon in hierarchical architecture for physical reinforcement learning: Photon intelligence
Makoto Naruse, Martin Berthel, Aurélien Drezet +3
Understanding and using natural processes for intelligent functionalities, referred to as natural intelligence, has recently attracted interest from a variety of fields, including…
Randomness in highly reflective silver nanoparticles and their localized optical fields
Makoto Naruse, Takeharu Tani, Hideki Yasuda +3
Reflection of near-infrared light is important for preventing heat transfer in energy saving applications. A large-area, mass-producible reflector that contains randomly distribute…
Chaotic oscillation and random-number generation based on nanoscale optical-energy transfer
Makoto Naruse, Song-Ju Kim, Masashi Aono +2
By using nanoscale energy-transfer dynamics and density matrix formalism, we demonstrate theoretically and numerically that chaotic oscillation and random-number generation occur i…