Reinforcement Learning in a Large Scale Photonic Network

Sheler Maktoobi; Louis Andreoli; Laurent Larger; Maxime Jacquot; Daniel Brunner

doi:10.1364/CLEOPR.2018.W1D.4

CLEO Pacific Rim Conference 2018
OSA Technical Digest (Optica Publishing Group, 2018),
paper W1D.4
•https://doi.org/10.1364/CLEOPR.2018.W1D.4

Reinforcement Learning in a Large Scale Photonic Network

Sheler Maktoobi, Louis Andreoli, Laurent Larger, Maxime Jacquot, and Daniel Brunner

Conference on Lasers and Electro-Optics/Pacific Rim 2018

Hong Kong China
29 July–3 August 2018
ISBN: 978-1-943580-45-3

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Machine Learning and Neural Networks in Photonics (W1D)

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S. Maktoobi, L. Andreoli, L. Larger, M. Jacquot, and D. Brunner, "Reinforcement Learning in a Large Scale Photonic Network," in CLEO Pacific Rim Conference 2018, OSA Technical Digest (Optica Publishing Group, 2018), paper W1D.4.

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Abstract

We experimentally create a neural network, implementing 2025 connections in parallel. We numerically validate the scheme for at least 34000 photonic neurons. We demonstrate photonic efficiently converging reinforcement learning, prediction a chaotic signal with.

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