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        <datestamp>2025-01-19T15:03:12Z</datestamp>
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          <dc:title>ゲームAIの局所戦略のSHAPによる説明</dc:title>
          <dc:title xml:lang="en">Explaining Local Strategy of Games using SHAP</dc:title>
          <jpcoar:creator>
            <jpcoar:creatorName>藤井, 慧</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Satoru, Fujii</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:subject subjectScheme="Other">ゲームプレイヤの評価・説明</jpcoar:subject>
          <datacite:description descriptionType="Other">ゲームの戦略の機械学習に関する研究はこれまで大きな発展を遂げてきたが，それに基づく強いゲーム AI の戦略を人間に解釈可能な形で説明する研究は進んでいない．本研究では，SHAP と呼ばれる手法を応用したゲーム AI の局所戦略の説明の具体的な実装法を提案し，実験を通じて具体的な分析の例を示した．</datacite:description>
          <datacite:description descriptionType="Other">Recent advances in game informatics enabled us to find strong strategies for a wide range of games. However, these strategies are usually hard to interpret for humans. In this paper, we propose a method to explain local strategies of games via SHAP, along with several experimental results.</datacite:description>
          <dc:publisher xml:lang="ja">情報処理学会</dc:publisher>
          <datacite:date dateType="Issued">2022-06-25</datacite:date>
          <dc:language>jpn</dc:language>
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          <jpcoar:sourceIdentifier identifierType="ISSN">2188-8736</jpcoar:sourceIdentifier>
          <jpcoar:sourceIdentifier identifierType="NCID">AA11362144</jpcoar:sourceIdentifier>
          <jpcoar:sourceTitle>研究報告ゲーム情報学（GI）</jpcoar:sourceTitle>
          <jpcoar:volume>2022-GI-48</jpcoar:volume>
          <jpcoar:issue>8</jpcoar:issue>
          <jpcoar:pageStart>1</jpcoar:pageStart>
          <jpcoar:pageEnd>6</jpcoar:pageEnd>
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            <datacite:date dateType="Available">2024-06-25</datacite:date>
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