DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Kim, Beomjoon | - |
dc.contributor.advisor | 김범준 | - |
dc.contributor.author | Jo, Heesang | - |
dc.date.accessioned | 2023-06-22T19:31:11Z | - |
dc.date.available | 2023-06-22T19:31:11Z | - |
dc.date.issued | 2023 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=1032331&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/308179 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 김재철AI대학원, 2023.2,[v, 38 p. :] | - |
dc.description.abstract | We propose a hierarchical planning algorithm that efficiently finds the optimal plan for the given planning problem. A key challenge to the hierarchical planning approach is that a higher-level plan may fail to properly guide the planning at the lower level. To handle this we view this problem as the balancing problem between exploration and exploitation and use the Monte-Carlo tree search algorithm to efficiently focus on seemingly promising high-level plans. We also present a theoretical analysis on the optimality of our algorithm and show that under certain conditions, our algorithm is guaranteed to find the optimal plan. We showed that our method outperforms existing algorithms in the continuous path planning domain. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Artificial intelligence▼aHierarchical planning▼aMonte-Carlo tree search | - |
dc.subject | 인공지능▼a계층적 계획법▼a몬테-카를로 트리 탐색 | - |
dc.title | Efficient planner using information of hierarchy and the Monte-Carlo tree search | - |
dc.title.alternative | 계층 정보와 몬테-카를로 트리 탐색 알고리즘을 이용한 효율적인 계획법 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :김재철AI대학원, | - |
dc.contributor.alternativeauthor | 조희상 | - |
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