Evaluating influence diagrams with decision circuits
Evaluating influence diagrams with decision circuits
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使用决策电路评估影响图
DOI：
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发表时间：
2007
期刊：
影响因子：
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通讯作者：
Ross D. Shachter
中科院分区：
文献类型：
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作者：
D. Bhattacharjya;Ross D. Shachter
虽然已经开发了一些相关的算法来评估影响图，利用图中的条件独立性，精确的解决方案仍然是棘手的许多重要问题。在本文中，我们引入决策电路作为一种手段，利用当地的结构通常发现的决策问题，并提高性能的影响图分析。这项工作建立在概率推理算法的基础上，使用算术电路来表示贝叶斯信念网络[Darwiche，2003]。一旦编译，这些算术电路有效地评估信念网络上的概率查询，并且已经开发了利用网络的全局和局部结构的方法。我们表明，决策电路可以以类似的方式构建，并承诺类似的好处。
Although a number of related algorithms have been developed to evaluate influence diagrams, exploiting the conditional independence in the diagram, the exact solution has remained intractable for many important problems. In this paper we introduce decision circuits as a means to exploit the local structure usually found in decision problems and to improve the performance of influence diagram analysis. This work builds on the probabilistic inference algorithms using arithmetic circuits to represent Bayesian belief networks [Darwiche, 2003]. Once compiled, these arithmetic circuits efficiently evaluate probabilistic queries on the belief network, and methods have been developed to exploit both the global and local structure of the network. We show that decision circuits can be constructed in a similar fashion and promise similar benefits.