no code implementations • 3 May 2023 • Honoka Shiratori, Hiroaki Shinkawa, André Röhm, Nicolas Chauvet, Etsuo Segawa, Jonathan Laurent, Guillaume Bachelier, Tomoki Yamagami, Ryoichi Horisaki, Makoto Naruse
Quantum processes can realize conflict-free joint decisions among two agents using the entanglement of photons or quantum interference of orbital angular momentum (OAM).
no code implementations • 20 Dec 2022 • Hiroaki Shinkawa, Nicolas Chauvet, André Röhm, Takatomo Mihana, Ryoichi Horisaki, Guillaume Bachelier, Makoto Naruse
In addition, we propose a multi-agent architecture in which agents are indirectly connected through quantum interference of light and quantum principles ensure the conflict-free property of state-action pair selections among agents.
no code implementations • 5 Aug 2022 • Hiroaki Shinkawa, Nicolas Chauvet, André Röhm, Takatomo Mihana, Ryoichi Horisaki, Guillaume Bachelier, Makoto Naruse
Second, to derive the optimal joint selection probability matrix, all players must disclose their probabilistic preferences.
no code implementations • 19 May 2022 • Takashi Urushibara, Nicolas Chauvet, Satoshi Kochi, Satoshi Sunada, Kazutaka Kanno, Atsushi Uchida, Ryoichi Horisaki, Makoto Naruse
Q-learning is a well-known approach in reinforcement learning that can deal with many states.
no code implementations • 2 May 2022 • Hiroaki Shinkawa, Nicolas Chauvet, Guillaume Bachelier, André Röhm, Ryoichi Horisaki, Makoto Naruse
Here, we theoretically derive conflict-free joint decision-making that can satisfy the probabilistic preferences of all individual players.
no code implementations • 30 Mar 2022 • Norihiro Okada, Tomoki Yamagami, Nicolas Chauvet, Yusuke Ito, Mikio Hasegawa, Makoto Naruse
In this study, we demonstrate a theoretical model to account for accelerating decision-making by correlated time sequence.
no code implementations • 2 Jul 2021 • Takashi Amakasu, Nicolas Chauvet, Guillaume Bachelier, Serge Huant, Ryoichi Horisaki, Makoto Naruse
In recent cross-disciplinary studies involving both optics and computing, single-photon-based decision-making has been demonstrated by utilizing the wave-particle duality of light to solve multi-armed bandit problems.
no code implementations • 26 May 2020 • Naoki Narisawa, Nicolas Chauvet, Mikio Hasegawa, Makoto Naruse
By exploiting ultrafast and irregular time series generated by lasers with delayed feedback, we have previously demonstrated a scalable algorithm to solve multi-armed bandit (MAB) problems utilizing the time-division multiplexing of laser chaos time series.
no code implementations • 24 May 2019 • Makoto Naruse, Takashi Matsubara, Nicolas Chauvet, Kazutaka Kanno, Tianyu Yang, Atsushi Uchida
Here we utilize chaotic time series generated experimentally by semiconductor lasers for the latent variables of GAN whereby the inherent nature of chaos can be reflected or transformed into the generated output data.
no code implementations • 12 Apr 2018 • Nicolas Chauvet, David Jegouso, Benoît Boulanger, Hayato Saigo, Kazuya Okamura, Hirokazu Hori, Aurélien Drezet, Serge Huant, Guillaume Bachelier, Makoto Naruse
The competitive multi-armed bandit (CMAB) problem is related to social issues such as maximizing total social benefits while preserving equality among individuals by overcoming conflicts between individual decisions, which could seriously decrease social benefits.