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Reinforcement Learning for Coherent Beam Combining

descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 2018Publisher:OSAJournal:CLEO Pacific Rim Conference
Authors: Henrik Tünnermann; Akira Shirakawa;

doi: 10.1364/cleopr.2018.w1a.2

Reinforcement Learning for Coherent Beam Combining

Abstract

Reinforcement learning has been shown to be capable of solving complex tasks. Here we show potential advantages and disadvantages in the context of phase control for coherent beam combining.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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