上下文相关时间概率模型构建的理论框架及其在规划投影中的应用
A Theoretical Framework for Context-Sensitive Temporal Probability Model Construction with Application to Plan Projection
摘要：
我们定义了一个上下文敏感的时间概率逻辑表示类的离散时间时间贝叶斯网络。上下文约束允许推理只集中在概率知识的相关部分。我们为我们的语言提供了声明性语义。我们提出了一个贝叶斯网络的构建算法，其生成的网络提供声音和完整的答案查询。我们使用逻辑编程中的相关概念来证明我们的方法。我们已经实现了贝叶斯网络的构造算法的理论的一个子集，并证明它的应用程序的问题，评估治疗急性心脏病的有效性。
英文摘要：
We define a context-sensitive temporal probability logic for representing classes of discrete-time temporal Bayesian networks. Context constraints allow inference to be focused on only the relevant portions of the probabilistic knowledge. We provide a declarative semantics for our language. We present a Bayesian network construction algorithm whose generated networks give sound and complete answers to queries. We use related concepts in logic programming to justify our approach. We have implemented a Bayesian network construction algorithm for a subset of the theory and demonstrate it's application to the problem of evaluating the effectiveness of treatments for acute cardiac conditions.
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。
