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Comparative analysis of Reinforcement Learning and Evolutionary Strategy in General Video Game Playing
https://ipsj.ixsq.nii.ac.jp/records/162612
https://ipsj.ixsq.nii.ac.jp/records/1626129fbfd8b0-b1b8-41b3-9b1b-2adb30c2760c
| 名前 / ファイル | ライセンス | アクション |
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IPSJ-Z78-5M-09.pdf (886.9 kB)
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Copyright (c) 2016 by the Information Processing Society of Japan
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| オープンアクセス | ||
| Item type | National Convention(1) | |||||||||||
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| 公開日 | 2016-03-10 | |||||||||||
| タイトル | ||||||||||||
| タイトル | Comparative analysis of Reinforcement Learning and Evolutionary Strategy in General Video Game Playing | |||||||||||
| 言語 | ||||||||||||
| 言語 | eng | |||||||||||
| キーワード | ||||||||||||
| 主題Scheme | Other | |||||||||||
| 主題 | 人工知能と認知科学 | |||||||||||
| 資源タイプ | ||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||||||||
| 資源タイプ | conference paper | |||||||||||
| 著者所属 | ||||||||||||
| 立命館大 | ||||||||||||
| 著者所属 | ||||||||||||
| 立命館大 | ||||||||||||
| 著者所属 | ||||||||||||
| 立命館大 | ||||||||||||
| 著者名 |
朱, 晉賢
× 朱, 晉賢
× ラック, ターウォンマット
× 原田, 智広
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| 論文抄録 | ||||||||||||
| 内容記述タイプ | Other | |||||||||||
| 内容記述 | This paper presents a comparative analysis between Reinforcement Learning (RL) and Evolutionary Strategy (ES) for training rollout bias in General Video Game Playing (GVGP). GVGP has become an emerging research field, where researchers attempt to develop AI programs that can play various types of video game without prior knowledge. Monte-Carlo Tree Search, which does not require explicit evaluation function, has been a popular technique in GVGP, and existing research has succeeded in improving its performance by biasing the rollouts with weights vector, which is trained by ES. This paper compares RL and ES, and investigates the advantages and disadvantages of both techniques as rollout bias training mechanism in the GVGP domain. | |||||||||||
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| 収録物識別子タイプ | NCID | |||||||||||
| 収録物識別子 | AN00349328 | |||||||||||
| 書誌情報 |
第78回全国大会講演論文集 巻 2016, 号 1, p. 163-164, 発行日 2016-03-10 |
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| 出版者 | ||||||||||||
| 言語 | ja | |||||||||||
| 出版者 | 情報処理学会 | |||||||||||
