(A) reinforcement learning approach to the path planning problem with backend information processing백엔드 정보 처리를 포함한 경로 탐색 문제에 대한 강화학습 접근법

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dc.contributor.advisorShin, Hayong-
dc.contributor.advisor신하용-
dc.contributor.authorMerve, Doganbas-
dc.date.accessioned2023-06-23T19:31:13Z-
dc.date.available2023-06-23T19:31:13Z-
dc.date.issued2022-
dc.identifier.urihttp://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=997797&flag=dissertationen_US
dc.identifier.urihttp://hdl.handle.net/10203/308799-
dc.description학위논문(석사) - 한국과학기술원 : 산업및시스템공학과, 2022.2,[iii, 20 p. :]-
dc.description.abstractThis research focuses on the path planning problem that emerges during the inspection of a Printed Circuit Board (PCB) at semiconductor fabs. The inspection process consists of two elements: the camera and the image processor. The camera visits and captures the predetermined locations on a PCB. The inspection is performed on this image by the backend image processor. The objective of the research is to minimize the makepsan of the inspection of a PCB. A reinforcement learning approach is proposed to solve the problem. Firstly, the 2-Opt heuristic method is adopted. A policy network and a state value network are trained on the paths provided by the 2-Opt in a supervised manner. The policy network provided comparable solutions to the target policy which is the 2-Opt heuristic. * The author of this thesis is a Global Korea Scholarship scholar sponsored by the Korean Government-
dc.languageeng-
dc.publisher한국과학기술원-
dc.title(A) reinforcement learning approach to the path planning problem with backend information processing-
dc.title.alternative백엔드 정보 처리를 포함한 경로 탐색 문제에 대한 강화학습 접근법-
dc.typeThesis(Master)-
dc.identifier.CNRN325007-
dc.description.department한국과학기술원 :산업및시스템공학과,-
dc.contributor.alternativeauthor메르베-
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