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Updated: Jul 14, 2025

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D2CFR:通过深度决斗神经网络,最大限度地减少反事实遗憾

Huale Li, Xuan Wang, Zengyue Guo

    IEEE transactions on neural networks and learning systems
    |October 6, 2023
    PubMed
    概括

    深度决斗CFR (D2CFR) 通过改进状态值估计来增强游戏理论,从而在不完美的信息游戏中实现更快的融合和更好的性能. 这种新的方法克服了现有的基于神经系统的方法的局限性.

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