Artificial Intelligence (AI) and Machine Learning (ML) approaches have emerged in the networking domain with great expectation. They can be broadly divided into AI/ML techniques for network engineering and management, network designs for AI/ML applications, and system concepts. AI/ML techniques for networking and management improve the way we address networking. They support efficient, rapid, and trustworthy engineering, operations, and management. As such, they meet the current interest in softwarization and network programmability that fuels the need for improved network automation in agile infrastructures, including edge and fog environments. Network design and optimization for AI/ML applications addresses the complementary topic of supporting AI/ML-based systems through novel networking techniques, including new architectures and algorithms. The third topic area is system implementation and open-source software development.

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客座社论特刊：人工智能和网络机器学习的发展

人工智能（AI）和机器学习（ML）方法已经在网络领域出现，并寄予厚望。它们可以大致分为用于网络工程和管理的AI / ML技术，用于AI / ML应用程序的网络设计以及系统概念。用于网络和管理的AI / ML技术改善了我们处理网络的方式。它们支持高效，快速和值得信赖的工程，运营和管理。这样，它们满足了当前对软化和网络可编程性的兴趣，从而激发了对包括边缘和雾环境在内的敏捷基础架构中改进的网络自动化的需求。针对AI / ML应用程序的网络设计和优化通过包括新架构和算法在内的新型联网技术解决了支持基于AI / ML的系统的补充主题。