The vision of autonomous systems is becoming increasingly important in many application areas, where the aim is to replace humans with agents. These include autonomous vehicles and other agents' applications in business processes and problem-solving. For networks, the increasing scale and operation and management (O&M) complexity drive the need for autonomous networks (AN). The technical objective of AN is to ensure trustworthy O&M without human intervention for higher efficiency and lower operating costs. However, realizing AN seems more difficult than autonomous vehicles. It encounters challenges of networks' structural and functional complexity, which operate as distributed dynamic systems governed by various technical and economic constraints. A key problem lies in formulating a rigorous development methodology that facilitates a seamless transition from traditional networks to AN. Central to this methodology is the definition of a reference architecture for network agents, which specifies the required functionalities for their realization, regardless of implementation choices. This article proposes a reference architecture characterizing main functional features, illustrating its application with network use cases. It shows how artificial intelligence components can be used to implement the required functionality and its coordination. The latter is achieved through the management and generation of shared domain-specific knowledge stored in long-term memory, ensuring the overall consistency of decisions and their execution. The article concludes with a discussion of architecture specialization for building network layer agents. It also identifies the main technical challenges ahead, such as satisfying essential requirements at development or runtime, as well as the issue of coordinating agents to achieve collective intelligence in meeting overall network goals.

翻译：自主系统的愿景在许多应用领域中日益重要，其目标是以智能体替代人类操作。这包括自动驾驶车辆以及智能体在业务流程和问题解决中的其他应用。对于网络而言，日益增长的规模及运维复杂性推动了对自主网络的需求。自主网络的技术目标是在无需人工干预的情况下实现可信赖的运维，从而提高效率并降低运营成本。然而，实现自主网络似乎比实现自动驾驶车辆更为困难。它面临着网络结构和功能复杂性的挑战，这些网络作为分布式动态系统运行，受各种技术和经济约束的制约。一个关键问题在于制定一种严格的开发方法论，以促进从传统网络到自主网络的无缝过渡。该方法论的核心是定义网络智能体的参考架构，该架构规定了实现所需的功能特性，而与具体实现选择无关。本文提出了一种表征主要功能特征的参考架构，并通过网络用例说明其应用。文章展示了如何利用人工智能组件来实现所需功能及其协调。后者通过管理和生成存储在长期记忆中的共享领域特定知识来实现，从而确保决策及其执行的全局一致性。文章最后讨论了构建网络层智能体的架构特化问题，并指出了面临的主要技术挑战，例如在开发或运行时满足基本要求，以及协调智能体以实现集体智能来达成整体网络目标的问题。