用于时空推理的规则引擎? [英] Rules engine for spatial and temporal reasoning?

问题描述

我有一个应用程序，该应用程序接收许多表征3D时空过程的数据.然后，它过滤这些基准并创建动作，然后将其发送到执行该动作的进程.冲洗并重复.

I have an application that receives a number of datums that characterize 3 dimensional spatial and temporal processes. It then filters these datums and creates actions which are then sent to processes that perform the actions. Rinse and repeat.

目前，我有一组自定义过滤器，它们可以执行许多复杂的时空计算.

At present, I have a collection of custom filters that perform a lot of complicated spatial/temporal calculations.

很多时候，当我与公司中的个人讨论系统时，他们会问我是否在使用规则引擎.

Many times as I discuss my system to individuals in my company, they ask if I'm using a rules engine.

我还没有找到能够在时间和空间上进行合理推理的规则引擎. (例如:两个3D实体何时关闭?3D实体A是否曾经包含在3D区域B中?如果实体C在实体D附近但相对于C朝后，则执行操作D.)

I have yet to find a rules engine that is able to reason well temporally and spatially. (Things like: When are two 3D entities ever close? Is 3D entity A ever contained in 3D region B? If entity C is near entity D but oriented backwards relative to C then perform action D.)

我过去曾经看过Drools，Cyc和Jess(例如3-4年前).现在该重新检查一下最新技术水平.有什么建议?您知道的任何标准都支持这种推理吗?有事实上的标准吗?有任何应用程序吗?

I have looked at Drools, Cyc, Jess in the past (say 3-4 years ago). It's time to re-examine the state of the art. Any suggestions? Any standards that you know of that support this kind of reasoning? Any defacto standards? Any applications?

谢谢！

推荐答案

前提-记住，基于SQL的 ¹ DBMS是(相当有能力的)推理引擎，从这些比较中可以看出在SQL和Prolog之间:

Premise - remember that a SQL-based¹ DBMS is a (quite capable) inference engine, as can be seen from these comparisons between SQL and Prolog:

• 序言到SQL转换器
• SQL和Prolog之间的差异

• prolog to SQL converter
• difference between SQL and Prolog

要专门解决您的时空应用，本书将帮助您:

To address specifically your spatio-temporal applications, this book will help:

• 时间数据和关系模型-详细调查 间隔和关系理论在时间数据库管理问题中的应用.

• TEMPORAL DATA AND THE RELATIONAL MODEL - A Detailed Investigation into the Application of Interval and Relation Theory to the Problem of Temporal Database Management.

也就是说，将间隔和关系理论结合起来可以有效地推理出时空问题(请参见

That is, combining Interval and Relation Theory is possible to reasoning about spatio-temporal problems effectively (see 5.2 Applications of Intervals).

当然，如果您的基于SQL的DBMS还没有配备间隔(和其他)运算符，则需要适当地扩展它(通过存储程序和/或用户定义的函数-UDF).

Of course, if your SQL-based DBMS is not (yet) equipped with interval (and other) operators you will need to extend it appropriately (via store-procedures and/or User-Defined Functions - UDFs).

更新:略读指出的论文朝着用于建筑物信息模型的3D空间查询语言)基本上可以完成我在上文中提到的工作:

Update: skimming the paper pointed out in comments by timemirror (Towards a 3D Spatial Query Language for Building Information Models) they do essentially what I touched on above:

(最后一页)

实施概念

执行摘要 将系统输入查询语言 根据查询执行 语言SQL，这是一种广泛使用的 已建立的领域标准 对象关系数据库.这 国际标准SQL:1999 将关系模型扩展到 包括面向对象的方面，例如 作为定义复杂的可能性 具有集成的抽象数据类型 方法.

The implementation of the abstract type system into a query language will be performed on the basis of the query language SQL, which is a widely established standard in the field of object-relational databases. The international standard SQL:1999 extends the relational model to include object-oriented aspects, such as the possibility to define complex abstract data types with integrated methods.

我不同意对象关系数据库"的术语(由于此处不合主题，但我认为其余的是相关的.)

I do not concur with the "object-relational database" terminology (for reason off-topic here) but I think the rest is pertinent.

更新:引用上述书中的3D和区间理论:

Update: a quote regardind 3D and interval theory from the book cited above:

注意:所有讨论的时间间隔 到目前为止可以认为是 一维的.但是，我们可能 要结合两个一维 形成二维的间隔 间隔.例如，一个矩形 地块可能被认为是 一个二维间隔，因为它 根据定义，是具有 长度和宽度，每个都是 基本上是一维间隔 沿某些轴测量.并且， 当然，我们可以将此想法扩展到任何 尺寸数量.例如，一个 (相当简单！)建筑可能是 被视为三维 间隔:这是一个有长度的物体， 宽度和高度，换句话说a 长方体. (更现实的是， 建筑可能被视为一套 几个重叠的长方体 各种方式.)等等.在什么 遵循，但是，我们将限制我们的 注意一维区间 具体来说，除非明确 陈述相反，我们 将省略一维" 限定词以简化操作.

NOTE: All of the intervals discussed so far can be thought of as one-dimensional. However, we might want to combine two one-dimensional intervals to form a twodimensional interval. For example, a rectangular plot of ground might be thought of as a two-dimensional interval, because it is, by definition, an object with length and width, each of which is basically a one-dimensional interval measured along some axis. And, of course, we can extend this idea to any number of dimensions. For example, a (rather simple!) building might be regarded as a three-dimensional interval: It is an object with length, width, and height, or in other words a cuboid. (More realistically, a building might be regarded as a set of several such cuboids that overlap in various ways.) And so on. In what follows, however, we will restrict our attention to one-dimensional intervals specifically, barring explicit statements to the contrary, and we will omit the "one-dimensional" qualifier for simplicity.

注意

1. 我写的是基于SQL的，而不是 relational ，因为存在使用完全脱离关系理论的DBMS的方法.

1. I wrote SQL-based and not relational because there are ways to use such DBMSes that completely deviate from relational theory.

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