Efficient planner using information of hierarchy and the Monte-Carlo tree search계층 정보와 몬테-카를로 트리 탐색 알고리즘을 이용한 효율적인 계획법

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 203
  • Download : 0
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.
Advisors
Kim, Beomjoonresearcher김범준researcher
Description
한국과학기술원 :김재철AI대학원,
Publisher
한국과학기술원
Issue Date
2023
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 김재철AI대학원, 2023.2,[v, 38 p. :]

Keywords

Artificial intelligence▼aHierarchical planning▼aMonte-Carlo tree search; 인공지능▼a계층적 계획법▼a몬테-카를로 트리 탐색

URI
http://hdl.handle.net/10203/308179
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=1032331&flag=dissertation
Appears in Collection
AI-Theses_Master(석사논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0