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dc.contributor.authorWei, Ting-Hanen_US
dc.contributor.authorWu, I-Chenen_US
dc.contributor.authorLiang, Chao-Chinen_US
dc.contributor.authorChiang, Bing-Tsungen_US
dc.contributor.authorTseng, Wen-Jieen_US
dc.contributor.authorYen, Shi-Jimen_US
dc.contributor.authorLee, Chang-Shingen_US
dc.date.accessioned2015-12-02T03:00:49Z-
dc.date.available2015-12-02T03:00:49Z-
dc.date.issued2014-01-01en_US
dc.identifier.isbn978-3-319-14923-3; 978-3-319-14922-6en_US
dc.identifier.issn1865-0929en_US
dc.identifier.urihttp://hdl.handle.net/11536/128467-
dc.description.abstractThis paper investigates job-level (JL) algorithms to analyze opening positions for Connect6. The opening position analysis is intended for opening book construction, which is not covered by this paper. In the past, JL proof-number search (JL-PNS) was successfully used to solve Connect6 positions. Using JL-PNS, many opening plays that lead to losses can be eliminated from consideration during the opening game. However, it is unclear how the information of unsolved positions can be exploited for opening book construction. For this issue, this paper first proposes four heuristic metrics when using JL-PNS to estimate move quality. This paper then proposes a JL upper confidence tree (JL-UCT) algorithm and some heuristic metrics, one of which is the number of nodes in each candidate move\'s subtree. In order to compare these metrics objectively, we proposed two kinds of measurement methods to analyze the suitability of these metrics when choosing best moves for a set of benchmark positions. The results show that for both metrics this node count heuristic metric for JL-UCT outperforms all the others, including the four for JL-PNS.en_US
dc.language.isoen_USen_US
dc.subjectJob-level computingen_US
dc.subjectopening book generationen_US
dc.subjectConnect6en_US
dc.subjectproof-number searchen_US
dc.subjectMonte-Carlo tree searchen_US
dc.subjectupper confidence bounden_US
dc.titleJob-Level Algorithms for Connect6 Opening Position Analysisen_US
dc.typeProceedings Paperen_US
dc.identifier.journalCOMPUTER GAMES, CGW 2014en_US
dc.citation.volume504en_US
dc.citation.spage29en_US
dc.citation.epage44en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000357394700003en_US
dc.citation.woscount0en_US
Appears in Collections:Conferences Paper