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Approximate Sufficient Statistics for Team Decision Problems

机译:团队决策问题的大致足够的统计数据

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Team decision problems are one of the fundamental problems in decentralized decision making. Because team decision problems are NP-hard, it is important to find methods for reducing their complexity. Wu and Lall gave a definition of sufficient statistics for team decision problems, and demonstrated that these statistics are sufficient for optimality, and possess other desirable properties such as being readily updated when additional information becomes available. More recently, Lemon and Lall defined weak sufficient statistics for team decision problems, and showed that these statistics are sufficient for optimality and necessary for simultaneous optimality with respect to all cost functions. This prior work studied the extent to which the complexity of team decision problems can be reduced while maintaining exact optimality. However, when faced with a computationally difficult problem, we are often willing to sacrifice exact optimality for significant reductions in complexity. In this paper we define approximate sufficient statistics, which are a generalization of weak team sufficient statistics. Then we prove that these statistics are quantifiably close to being optimal.
机译:团队决策问题是分散决策中的基本问题之一。因为团队决策问题是NP - 硬,所以要找到减少复杂性的方法很重要。吴和Lall对团队决策问题的充分统计数据进行了定义,并证明这些统计数据足以使得最优性,并且在附加信息变得可用时,可以容易更新其他所需的性质。最近,柠檬和leall界定了团队决策问题的弱足够的统计数据,并且表明这些统计数据足以使得最优能力和同时最优能力的最优函数。此前的工作研究了在保持精确的最优性的同时可以减少团队决策问题的复杂性的程度。然而,当面对计算困难的问题时,我们往往愿意牺牲精确的最优性以显着减少复杂性。在本文中,我们定义了近似统计数据,这是弱团队充足统计数据的概括。然后,我们证明了这些统计数据量是最靠近的最佳状态。

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