Probabilistic Sentential Decision Diagrams
Probabilistic Sentential Decision Diagrams
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概率句子决策图
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Adnan Darwiche
中科院分区：
文献类型：
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作者：
D. Kisa;Guy Van den Broeck;Arthur Choi;Adnan Darwiche
我们提出了概率句子决策图（PSDD）：在给定命题理论的模型上定义的概率分布的完整和规范表示。 PSDD的每个参数都可以看作是在相应的句子决策图（SDD）中做出决定的（条件）概率。 SDD本身是最近提出的命题理论的完整和规范表示。我们探索了PSDD的许多有趣属性，包括独立的属性。我们证明PSDD是可拖动的表示。我们进一步展示了如何通过完整数据有效地以封闭形式有效地估计PSDD的参数。当我们拥有域逻辑约束的知识（先验）时，我们会经验评估从数据中学到的PS-DD的质量。
We propose the Probabilistic Sentential Decision Diagram (PSDD): A complete and canonical representation of probability distributions defined over the models of a given propositional theory. Each parameter of a PSDD can be viewed as the (conditional) probability of making a decision in a corresponding Sentential Decision Diagram (SDD). The SDD itself is a recently proposed complete and canonical representation of propositional theories. We explore a number of interesting properties of PSDDs, including the independencies that underlie them. We show that the PSDD is a tractable representation. We further show how the parameters of a PSDD can be efficiently estimated, in closed form, from complete data. We empirically evaluate the quality of PS-DDs learned from data, when we have knowledge, a priori, of the domain logical constraints.