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dc.contributor.authorChang, Chia-Chuanen_US
dc.contributor.authorWei, Ting-Hanen_US
dc.contributor.authorWu, I-Chenen_US
dc.date.accessioned2018-08-21T05:56:50Z-
dc.date.available2018-08-21T05:56:50Z-
dc.date.issued2016-01-01en_US
dc.identifier.issn2376-6816en_US
dc.identifier.urihttp://hdl.handle.net/11536/146720-
dc.description.abstractRecently, Wu et al. introduced a general approach based on distributed computing named Job-Level (JL) Computing. JL Computing has been successfully used to construct the opening books of game-playing programs. In order to support large-scale computing problems such as solving 7x7 killall-Go, or building opening books for 9x9 Go or Connect6, record databases are used to store JL computing results. In this paper, we further design a mechanism that combines the JL computing system with BOINC (Berkeley Open Infrastructure for Network Computing), so that we can leverage more computing power from volunteers to solve even larger problems. A preliminary experiment has been done to demonstrate the feasibility of the design.en_US
dc.language.isoen_USen_US
dc.subjectJob-Level computingen_US
dc.subjectvolunteer computingen_US
dc.subjectBOINCen_US
dc.subjectkillall-Goen_US
dc.titleJob-Level Computing With BOINC Supporten_US
dc.typeProceedings Paperen_US
dc.identifier.journal2016 CONFERENCE ON TECHNOLOGIES AND APPLICATIONS OF ARTIFICIAL INTELLIGENCE (TAAI)en_US
dc.citation.spage200en_US
dc.citation.epage206en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000406594200027en_US
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