论文标题

信息分解的游戏值

Values of Games for Information Decomposition

论文作者

Kroupa, Tomáš, Vannucci, Sara, Votroubek, Tomáš

论文摘要

信息分解问题需要将输入变量和目标变量之间的相互信息的添加性分解为非负项。最近引入的解决方案是信息归因,涉及莎普利式的价值,以测量与输入随机矢量的关节概率分布和目标变量相关的预测因子在联盟游戏中的影响。在原始问题的推动下,我们考虑了一般的联盟游戏,其中玩家形成了布尔代数,而联盟是相应的下集。这使我们能够详细研究称为值的各种单值解决方案概念。也就是说,我们专注于可以代表信息分解问题解决方案(例如随机订单值或共享值)的值类别的类别。我们扩展了仅针对标准联盟游戏而闻名的某些类别值的公理表征。

The information decomposition problem requires an additive decomposition of the mutual information between the input and target variables into nonnegative terms. The recently introduced solution to this problem, Information Attribution, involves the Shapley-style value measuring the influence of predictors in the coalitional game associated with the joint probability distribution of the input random vector and the target variable. Motivated by the original problem, we consider a general setting of coalitional games where the players form a boolean algebra, and the coalitions are the corresponding down-sets. This enables us to study in detail various single-valued solution concepts, called values. Namely, we focus on the classes of values that can represent very general alternatives to the solution of the information decomposition problem, such as random-order values or sharing values. We extend the axiomatic characterization of some classes of values that were known only for the standard coalitional games.

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