Abstract This article presents a method for estimating team formation based on a Markov chains games approach. The proposed approach represents the coalition structure using the Pareto front and naturally solves two fundamental problems in team formation: the coalition value computation and the payoff distribution. Central to this endeavor is the problem of finding the strong Nash equilibrium for which we employ the Newton optimization method. We use the Tikhonov regularization for ensuring the existence of a unique strong Nash equilibrium. The visualization technique plays a key role in helping decision-makers for team formation. An application example analyzes the optimal bundling strategies for a multiservice monopolist bank.

中文翻译：

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基于马尔可夫链博弈方法的团队组建方法

摘要 本文提出了一种基于马尔可夫链博弈方法的团队形成估计方法。所提出的方法使用帕累托前沿表示联盟结构，自然地解决了团队组建中的两个基本问题：联盟价值计算和收益分布。这项工作的核心是找到我们采用牛顿优化方法的强纳什均衡的问题。我们使用 Tikhonov 正则化来确保存在唯一的强纳什均衡。可视化技术在帮助决策者组建团队方面发挥着关键作用。一个应用实例分析了多服务垄断银行的最优捆绑策略。