Under Consideration for Publication in Theory and Practice of Logic Programming on the Implementation of the Probabilistic Logic Programming Language Problog
Under Consideration for Publication in Theory and Practice of Logic Programming on the Implementation of the Probabilistic Logic Programming Language Problog
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考虑在逻辑编程理论与实践中发表关于概率逻辑编程语言Problog的实现
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通讯作者：
Ricardo Rocha
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作者：
Angelika Kimmig;Bart Demoen;Luc De Raedt;Vítor Santos Costa;Ricardo Rocha
在过去的几年里，人们对概率逻辑学习和统计关系学习领域的兴趣激增。在这一努力中，发展了许多概率逻辑。ProbLog是Prolog最近的一个概率扩展，其动机是挖掘大型生物网络。在ProbLog中，事实可以用概率来标记。这些事实被视为相互独立的随机变量，表明这些事实是否属于随机抽样程序。可以向ProbLog程序提出不同类型的查询。我们介绍了允许有效执行这些查询的算法，讨论了它们在YAP-Prolog系统之上的实现，并在生物实体的大型网络环境中评估了它们的性能。
The past few years have seen a surge of interest in the field of probabilistic logic learning and statistical relational learning. In this endeavor, many probabilistic logics have been developed. ProbLog is a recent probabilistic extension of Prolog motivated by the mining of large biological networks. In ProbLog, facts can be labeled with probabilities. These facts are treated as mutually independent random variables that indicate whether these facts belong to a randomly sampled program. Different kinds of queries can be posed to ProbLog programs. We introduce algorithms that allow the efficient execution of these queries, discuss their implementation on top of the YAP-Prolog system, and evaluate their performance in the context of large networks of biological entities.