{"title":"Reinforcement Learning for Coherent Beam Combining","authors":"H. Tünnermann, A. Shirakawa","doi":"10.1364/CLEOPR.2018.W1A.2","DOIUrl":null,"url":null,"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.","PeriodicalId":184212,"journal":{"name":"2018 Conference on Lasers and Electro-Optics Pacific Rim (CLEO-PR)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Conference on Lasers and Electro-Optics Pacific Rim (CLEO-PR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1364/CLEOPR.2018.W1A.2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
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.