论文标题
Tyche：Python中的概率推理和信念建模的库
Tyche: A library for probabilistic reasoning and belief modelling in Python
论文作者
论文摘要
本文介绍了Tyche，这是一个Python图书馆，可通过建设，查询和学习信仰模型来促进不确定世界中的概率推理。 Tyche使用Aleatoric Description Logic（ADL），该逻辑（ADL）在其评估中比其他描述逻辑提供了计算优势。可以通过定义个人类别，关于他们的概率信念（概念）以及它们之间的概率关系（角色）来简洁地创建Tyche信仰模型。我们还引入了一种观察传播方法，以促进从复杂的ADL观察中学习。提供了Tyche的演示，以预测匿名消息的作者，并从匿名消息中提取作者写作倾向。 Tyche有可能协助开发专家系统，知识提取系统和代理商，以使用不完整和概率信息玩游戏。
This paper presents Tyche, a Python library to facilitate probabilistic reasoning in uncertain worlds through the construction, querying, and learning of belief models. Tyche uses aleatoric description logic (ADL), which provides computational advantages in its evaluation over other description logics. Tyche belief models can be succinctly created by defining classes of individuals, the probabilistic beliefs about them (concepts), and the probabilistic relationships between them (roles). We also introduce a method of observation propagation to facilitate learning from complex ADL observations. A demonstration of Tyche to predict the author of anonymised messages, and to extract author writing tendencies from anonymised messages, is provided. Tyche has the potential to assist in the development of expert systems, knowledge extraction systems, and agents to play games with incomplete and probabilistic information.
