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Strategic search in strategic interaction between parties

机译:各方之间战略互动中的战略搜索

摘要

Disclosed herein is a method, system, and apparatus comprising a computer program encoded on a computer storage medium for performing reflective performance regression minimization (CRF) for strategic search in strategic interactions between two or more parties. One of the methods includes the following: multiple regret samples-multiple regret samples obtained in two or more iterations of the CRF algorithm in a strategy search in strategic interaction between two or more parties-in a first data store. To store; Storing a number of strategic samples in a second data store; Updating a parameter of the first neural network to predict a regret value of a possible action in a party''s state based on a number of regret samples in the first data store; And updating the parameters of the second neural network to predict the strategic value of a possible action in the state of the party based on a number of strategy samples in the second data store.
机译:本文公开了一种方法,系统和装置,其包括在计算机存储介质上编码的计算机程序,该计算机程序用于在两个或多个参与方之间的战略交互中执行反射性能回归最小化(CRF)以进行战略搜索。一种方法包括以下内容:多个后悔样本-在第一数据存储中,在两个或多个参与方之间的战略交互中的策略搜索中,在CRF算法的两个或多个迭代中获得的多个后悔样本。储藏;在第二个数据存储中存储大量战略样本;更新所述第一神经网络的参数以基于所述第一数据存储中的多个后悔样本来预测一方状态下可能动作的后悔值;并且基于第二数据存储中的多个策略样本来更新第二神经网络的参数,以预测当事人状态下可能采取的行动的战略价值。

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