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Pob-CFR: A Population-Based Counterfactual Regret Minimization Approach for Strategy Optimization in Two-Player Zero-Sum Imperfect-Information Games.

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Title: Pob-CFR: A Population-Based Counterfactual Regret Minimization Approach for Strategy Optimization in Two-Player Zero-Sum Imperfect-Information Games.
Authors: Zhang, Lei1,2, Cai, Dingzhong2,3, Wang, Xuan2,3, xuan_wang@cs.hitsz.edu.cn
Source: Applied Sciences (2076-3417); Jun2026, Vol. 16 Issue 11, p5711, 23p
Database: Applied Science & Technology Source
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An: 194780317
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Pob-CFR: A Population-Based Counterfactual Regret Minimization Approach for Strategy Optimization in Two-Player Zero-Sum Imperfect-Information Games.
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  Data: <searchLink fieldCode="AU" term="%22Zhang%2C+Lei%22">Zhang, Lei</searchLink><relatesTo>1,2</relatesTo><br /><searchLink fieldCode="AU" term="%22Cai%2C+Dingzhong%22">Cai, Dingzhong</searchLink><relatesTo>2,3</relatesTo><br /><searchLink fieldCode="AU" term="%22Wang%2C+Xuan%22">Wang, Xuan</searchLink><relatesTo>2,3</relatesTo>, <i>xuan_wang@cs.hitsz.edu.cn</i>
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.3390/app16115711
    Languages:
      – Code: eng
        Text: English
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        PageCount: 23
        StartPage: 5711
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      – TitleFull: Pob-CFR: A Population-Based Counterfactual Regret Minimization Approach for Strategy Optimization in Two-Player Zero-Sum Imperfect-Information Games.
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            NameFull: Zhang, Lei
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            NameFull: Cai, Dingzhong
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            NameFull: Wang, Xuan
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            – D: 01
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              Text: Jun2026
              Type: published
              Y: 2026
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              Value: 16
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              Value: 11
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