分层多叉树网络的增量式动态构造
Incremental Dynamic Construction of Layered Polytree Networks
摘要：
某些类别的问题，包括感知数据理解，机器人技术，发现和学习，可以表示为增量，动态构建的信念网络。这些自动构建的网络可以动态地扩展和修改，因为新的个人的证据变得可用。本文的主要结果是单连通多叉树网络的增量扩展，以这样的方式，网络保持其单连通多叉树结构的变化后。该算法是确定性的，并且保证具有单节点添加的复杂性，该复杂性最多与网络的节点数量（或大小）成正比。通过维护路径信息可以实现额外的加速。尽管其增量和动态的性质，该算法也可以用于概率推理的信念网络的方式类似于其他精确推理算法。
英文摘要：
Certain classes of problems, including perceptual data understanding, robotics, discovery, and learning, can be represented as incremental, dynamically constructed belief networks. These automatically constructed networks can be dynamically extended and modified as evidence of new individuals becomes available. The main result of this paper is the incremental extension of the singly connected polytree network in such a way that the network retains its singly connected polytree structure after the changes. The algorithm is deterministic and is guaranteed to have a complexity of single node addition that is at most of order proportional to the number of nodes (or size) of the network. Additional speed-up can be achieved by maintaining the path information. Despite its incremental and dynamic nature, the algorithm can also be used for probabilistic inference in belief networks in a fashion similar to other exact inference algorithms.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
