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机译:一个蒙特卡罗神经虚拟自助式自助方法,以近期信息动态游戏近似纳什均衡
College of Computer Science and Technology Zhejiang University Hangzhou 310027 China;
College of Computer Science and Technology Zhejiang University Hangzhou 310027 China;
College of Computer Science and Technology Zhejiang University Hangzhou 310027 China;
College of Computer Science and Technology Zhejiang University Hangzhou 310027 China;
College of Computer Science and Technology Zhejiang University Hangzhou 310027 China;
College of Computer Science and Technology Zhejiang University Hangzhou 310027 China;
College of Computer Science and Technology Zhejiang University Hangzhou 310027 China;
approximate Nash Equilibrium; imperfect-information games; dynamic games; Monte Carlo tree search; Neural Fictitious Self-Play; reinforcement learning;
机译:减少静态博弈中近似纳什均衡的图形模型和遗传算法的方法
机译:减少静态博弈中近似纳什均衡的图形模型和遗传算法的方法
机译:网络游戏的动力学和纳什均衡
机译:基于Monte Carlo仿真的特派团成功率和随机化混合纳什均衡策略的罚款
机译:下个月将提供使用神经网络虚拟自玩的不完全信息游戏均衡解决方案的计算使用统计信息
机译:蛋白质组学生物标志物的贝叶斯分类使用近似贝叶斯计算-马尔可夫链的反应监测数据蒙特卡洛方法
机译:不完全信息游戏中的蒙特卡洛树搜索