通过动态偏好建模实现IoT的上下文感知
Context-awareness of the IoT through the on-the-fly preference modeling
摘要：
必须在分布式计算范式中考虑属于物联网网络的事物的上下文感知。在本文中，我们建议使用图变换和时序逻辑作为一个正式的框架，知识表示的用户/居民的行为在多智能体系统。物联网网络被认为是图结构。动态偏好模型，理解为在选择的优先级，也介绍了。偏好模型是基于形式逻辑的行为观测结果，由软件代理实时构建。软件代理收集有关用户偏好的逻辑规范方面表示的知识，以及建议在飞行中的未来行为的逻辑推理过程的基础上，使用语义tableaux方法。预测过程是物联网系统中一些新的重要事件的结果，这些事件应该满足响应。由于与物理环境交互的网络系统无处不在，因此非常需要开发将整个物联网系统作为上下文感知系统的技术。形式化方法提高了系统的可信度。提供了一个简单但说明性的例子。
英文摘要：
The context-awareness of things that belong to IoT networks have to be considered in a distributed computation paradigm. In the paper we suggest the use of graph transformations and temporal logic as a formal framework for a knowledge representation of user/inhabitant behaviors in multi-agent systems. IoT networks are considered as graph structures. Dynamic preference models, understood as a priority in the selecting, is also introduced. Preference models as a result of observed behaviors base on formal logic, and they are built on-the-fly by software agents. Software agents gather knowledge about user preferences expressed in terms of logical specifications as well as suggest on-the-fly future behavior basing on the logical inference process using the semantic tableaux method. The predictive processes are result of some new and important events in the context of IoT systems that should meet a response. Due to the ubiquitous availability of cyber systems that interact with physical environments, there is a great need to develop technologies that target the whole IoT system as a context-awareness system. Formal approach increases the trustworthy of a system. A simple yet illustrative example is provided.
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。
