Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 서일홍 | - |
dc.date.accessioned | 2020-10-28T00:51:43Z | - |
dc.date.available | 2020-10-28T00:51:43Z | - |
dc.date.issued | 2019-11 | - |
dc.identifier.citation | 대한전자공학회 학술대회, Page. 730-734 | en_US |
dc.identifier.uri | http://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE09282378 | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/155009 | - |
dc.description.abstract | Many real-world planning problems require choosing actions in a continuous action space. The continuous action space is so large that it is often discretized using domain knowledge. However, discretization of action space causes loss of information. There is a kernel based MCTS algorithm that solves this problem through similarity between actions and finds a good action in the continuous action space. However, the algorithm does not take into account the current state and the result of taking action. This problem leads the quite inefficient action search. In this paper, we use deep neural networks to solve these problems and propose a more efficient action search algorithm. | en_US |
dc.description.sponsorship | 이 연구는 2019년도 산업통상자원부 및 산업기술 평가관리원(KEIT) 연구비 지원을 받아 수행된 연구입니다.(10080638) | en_US |
dc.language.iso | ko_KR | en_US |
dc.publisher | 대한전자공학회 | en_US |
dc.title | 딥 러닝 기반의 행동 간 유사도 예측을 통한 연속 행동 공간에서의 최적 행동 탐색 | en_US |
dc.title.alternative | Action Search in Continuous Action Space by Predicting Similarity Between Actions based on Deep Learning | en_US |
dc.type | Article | en_US |
dc.relation.page | 730-734 | - |
dc.contributor.googleauthor | 정영빈 | - |
dc.contributor.googleauthor | 김민구 | - |
dc.contributor.googleauthor | 박지수 | - |
dc.contributor.googleauthor | 서일홍 | - |
dc.contributor.googleauthor | Jeong, Yeongbin | - |
dc.contributor.googleauthor | Kim, Mingu | - |
dc.contributor.googleauthor | Park, Jisoo | - |
dc.contributor.googleauthor | Suh, Il Hong | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF ENGINEERING[S] | - |
dc.sector.department | DEPARTMENT OF ELECTRONIC ENGINEERING | - |
dc.identifier.pid | ihsuh | - |
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