编译可能性网络：可能性推理的替代方法
Compiling Possibilistic Networks: Alternative Approaches to Possibilistic Inference
摘要：
定性可能性网络，又称最小可能性网络，是可能性理论框架中处理不确定信息的重要工具。尽管它们的重要性，只有连接树适应已被提出了精确的推理与这样的网络。本文探讨了使用编译技术的替代算法。我们首先提出了标准的基于编译的概率方法的可能性适应。然后，我们开发了一种新的，纯粹的可能性，方法的基础上的初始网络转换成一个可能性的基础。一项比较研究表明，后者比概率方法的可能性适应性更好。这一结果也得到了实验结果的证实。
英文摘要：
Qualitative possibilistic networks, also known as min-based possibilistic networks, are important tools for handling uncertain information in the possibility theory frame- work. Despite their importance, only the junction tree adaptation has been proposed for exact reasoning with such networks. This paper explores alternative algorithms using compilation techniques. We first propose possibilistic adaptations of standard compilation-based probabilistic methods. Then, we develop a new, purely possibilistic, method based on the transformation of the initial network into a possibilistic base. A comparative study shows that this latter performs better than the possibilistic adap- tations of probabilistic methods. This result is also confirmed by experimental results.
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