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A Compact Representation Scheme of Coalitional Games Based on Multi-Terminal Zero-Suppressed Binary Decision Diagrams

机译:基于多终端零抑制二元决策图的联盟博弈的紧凑表示方案

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Coalitional games, including Coalition Structure Generation (CSG), have been attracting considerable attention from the AI research community. Traditionally, the input of a coalitional game is a black-box function called a characteristic function. Previous studies have found that many problems in coalitional games tend to be computationally intractable in this black-box function representation. Recently, several concise representation schemes for a characteristic function have been proposed. Among them, a synergy coalition group (SCG) has several good characteristics, but its representation size tends to be large compared to other representation schemes. We propose a new concise representation scheme for a characteristic function based on a Zero-suppressed Binary Decision Diagram (ZDD) and a SCG. We show our scheme (i) is fully expressive, (ii) can be exponentially more concise than the SCG representation, (iii) can solve core-related problems in polynomial time in the number of nodes, and (iv) can solve a CSG problem reasonably well by utilizing a MIP formulation. A Binary Decision Diagram (BDD) has been used as unified infrastructure for representing/manipulating discrete structures in such various domains in AI as data mining and knowledge discovery. Adapting this common infrastructure brings up the opportunity of utilizing abundant BDD resources and cross-fertilization with these fields.
机译:包括联盟结构生成(CSG)在内的联盟游戏已引起AI研究界的极大关注。传统上,联盟游戏的输入是称为特征函数的黑盒函数。先前的研究发现,在这种黑盒函数表示中,联盟游戏中的许多问题在计算上往往难以解决。最近,已经提出了几种用于特征函数的简洁表示方案。其中,协同联盟组织(SCG)具有几个良好的特征,但是与其他代表方案相比,其代表规模往往更大。我们提出了一种基于零抑制二进制决策图(ZDD)和SCG的特征函数的简洁表示方案。我们证明了我们的方案(i)具有充分的表现力;(ii)可以比SCG表示更简洁;(iii)可以解决多项式时间内与节点数有关的核心相关问题;(iv)可以解决CSG通过使用MIP配方合理地解决了这个问题。二进制决策图(BDD)已被用作统一的基础结构,用于表示/操纵AI各个领域(如数据挖掘和知识发现)中的离散结构。适应这种通用基础设施将带来利用丰富的BDD资源和与这些领域交叉施肥的机会。

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