@inproceedings{oai:ipsj.ixsq.nii.ac.jp:00192075,
 author = {Chung-Chin, Shih and Ting, han Wei and Zheng-Yuan, Lee and I-Chen, Wu and Chung-Chin, Shih and Ting, han Wei and Zheng-Yuan, Lee and I-Chen, Wu},
 book = {ゲームプログラミングワークショップ2018論文集},
 month = {Nov},
 note = {This paper describes how the job-level computation system is used as a game playing agent, with a 90% win rate for Connect6 tournaments on the website Little Golem between the years 2009 to 2018. In addition, we also construct a win/loss database as an add-on to the existing job-level computation system. This database helps save precious computing resource when encountering previously solved game positions. In the experiments, a benchmark of 32 Connect6 openings is used. The results show that there are about 94.2% and 96.5% of the jobs can be conserved in JL-PNS and JL-UCT respectively for the benchmark when applying the win/loss database. Moreover, we discuss the issues about Graph Interaction Problem and how we generate hash keys of win/loss database., This paper describes how the job-level computation system is used as a game playing agent, with a 90% win rate for Connect6 tournaments on the website Little Golem between the years 2009 to 2018. In addition, we also construct a win/loss database as an add-on to the existing job-level computation system. This database helps save precious computing resource when encountering previously solved game positions. In the experiments, a benchmark of 32 Connect6 openings is used. The results show that there are about 94.2% and 96.5% of the jobs can be conserved in JL-PNS and JL-UCT respectively for the benchmark when applying the win/loss database. Moreover, we discuss the issues about Graph Interaction Problem and how we generate hash keys of win/loss database.},
 pages = {192--198},
 publisher = {情報処理学会},
 title = {Playing Games with the Job-Level Computation System},
 volume = {2018},
 year = {2018}
}