Query: Decision making chaotic semiconductor laser

Candidate papers:

abstract: We investigate the effect of a memory parameter on the performance of adaptive decision making using a tug of war method with the chaotic oscillatory dynamics of a semiconductor laser. We experimentally generate chaotic temporal waveforms of the semiconductor laser with optical feedback and apply them for adaptive decision making in solving a multiarmed bandit problem that aims at maximizing the total reward from slot machines whose hit probabilities are dynamically switched. We examine the dependence of making correct decisions on different values of the memory parameter. The degree of adaptivity is found to be enhanced with a smaller memory parameter, whereas the degree of convergence to the correct decision is higher for a larger memory parameter. The relations among the adaptivity, environmental changes, and the difficulties of the problem are also discussed considering the requirement of past decisions. This examination of ultrafast adaptive decision making highlights the importance of memorizing past events and paves the way for future photonic intelligence.
author_names: Takatomo Mihana

Yuta Terashima

Makoto Naruse

Song-Ju Kim

Atsushi Uchida
title: Memory Effect on Adaptive Decision Making with a Chaotic Semiconductor Laser
venue: Complex.
year: 2018

author_names: Akihiro Oda

Takatomo Mihana

Makoto Naruse

Atsushi Uchida
title: Investigation of decision making without prior knowledge using a chaotic semiconductor laser
year: 2018

author_names: Akihiro Oda

Takatomo Mihana

Kazutaka Kanno

Makoto Naruse

Atsushi Uchida
title: Decision making using chaotic semiconductor laser in bandit problem with variable hit probabilities
year: 2020

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author_names: Takatomo Mihana

Yuta Terashima

Makoto Naruse

Song-Ju Kim

Atsushi Uchida
title: Performance evaluation of decision making using chaotic semiconductor laser based on tug of war theory
year: 2017

author_names: Mihana Takatomo

Tera Yuta

Naruse Makoto

Kim Song-Ju

Uchida Atsushi
title: Adaptivity and convergence characteristics of decision making using chaotic semiconductor laser
year: 2017

author_names: Takatomo Mihana

Yuta Terashima

Atsushi Uchida

Makoto Naruse

Song-Ju Kim
title: Investigation of adaptation of ultrafast decision making using a chaotic semiconductor laser
year: 2017

abstract: We numerically and experimentally demonstrate the utilization of the synchronization of chaotic lasers for decision making. We perform decision making to solve the multi armed bandit problem using lag synchronization of chaos in mutually coupled semiconductor lasers. We observe the spontaneous exchanges of the leader laggard relationship under lag synchronization of chaos, and we find that the leader laser can be controlled by changing the coupling strengths between the two lasers. To solve the multi armed bandit problem, we select one of the slot machines with unknown hit probabilities based only on the identity of the leader laser while reconfiguring the coupling strength to determine the correct decision. We successfully perform an on line experimental demonstration of the decision making based on the two laser coupled architecture. This is the first time that synchronization in chaotic lasers is utilized for decision making, and this study paves the way for novel resources for future photonic intelligence.
author_names: Takatomo Mihana

Yusuke Mitsui

Mizuho Takabayashi

Kazutaka Kanno

Satoshi Sunada

Makoto Naruse

Atsushi Uchida
title: Decision making for the multi armed bandit problem using lag synchronization of chaos in mutually coupled semiconductor lasers.
venue: Optics express
year: 2019

abstract: Reinforcement learning involves decision making in dynamic and uncertain environments and constitutes an important element of artificial intelligence (AI) In this work, we experimentally demonstrate that the ultrafast chaotic oscillatory dynamics of lasers efficiently solve the multi armed bandit problem (MAB) which requires decision making concerning a class of difficult trade offs called the exploration exploitation dilemma. To solve the MAB, a certain degree of randomness is required for exploration purposes. However, pseudorandom numbers generated using conventional electronic circuitry encounter severe limitations in terms of their data rate and the quality of randomness due to their algorithmic foundations. We generate laser chaos signals using a semiconductor laser sampled at a maximum rate of 100 GSample/s, and combine it with a simple decision making principle called tug of war with a variable threshold, to ensure ultrafast, adaptive, and accurate decision making at a maximum adaptation speed of 1 GHz. We found that decision making performance was maximized with an optimal sampling interval, and we highlight the exact coincidence between the negative autocorrelation inherent in laser chaos and decision making performance. This study paves the way for a new realm of ultrafast photonics in the age of AI, where the ultrahigh bandwidth of light wave can provide new value.
author_names: Makoto Naruse

Yuta Terashima

Atsushi Uchida

Song-Ju Kim
title: Ultrafast photonic reinforcement learning based on laser chaos
venue: Scientific Reports
year: 2017

author_names: Takatomo Mihana

Kiyohiro Fujii

Kazutaka Kanno

Makoto Naruse

Atsushi Uchida
title: Decision making using semiconductor laser network based on tug of war theory
year: 2020

abstract: Photonic reinforcement learning and decision making has been used to solve multi armed bandit problem. We propose a method of decision making using lag synchronization of chaos in mutually coupled semiconductor lasers. We numerically investigate the performance of decision making by changing the sampling interval of chaotic temporal waveforms.
author_names: Takatomo Mihana

Yusuke Mitsui

Mizuho Takabayashi

Kazutaka Kanno

Makoto Naruse

Atsushi Uchida
title: Decision making using lag synchronization of chaos in mutually coupled semiconductor lasers
year: 2019