Recent advancements in AI have led to the development of specialized systems related to multi-agent systems (MAS). However, the inherently collaborative nature of agents is often overlooked, and many of these specialized systems are used as components by other AI systems. From a software engineering perspective, this context can benefit from aligning the architectural characteristics of distributed systems with the inherently distributed nature of MAS. We propose that introducing a minimal set of agent-related concepts into the Distributed Systems (DS) domain can improve the engineering of modern MAS by leveraging techniques from DS engineering with established agent theory. In this study, we recapitulated the common origins of MAS and DS by drawing architectural parallels to establish a unified engineering approach. We then defined a minimal set of agent concepts to perform two practical studies on leveraging MAS development. First, we incorporated these concepts into a DS architectural pattern to design a distributed MAS. We then used these concepts in a graduate course to teach MAS engineering to students with no prior knowledge of agent theory. The learning outcomes from both courses included successful MAS implementation using DS tools and techniques. Although more than two-thirds of these students had no practical experience in developing distributed systems, the average final grade in both courses was above 80\%, thus validating our approach. Finally, we discuss how this study supports the development of advanced systems using modern AI techniques consistently with established agent-related research while leveraging established DS techniques and concepts.

翻译：人工智能的最新进展推动了与多智能体系统（MAS）相关的专业化系统的发展。然而，智能体固有的协作特性常被忽视，且许多此类专业化系统被用作其他AI系统的组件。从软件工程视角来看，这种情境可通过将分布式系统的架构特征与MAS的分布式本质相协调而受益。我们提出，在分布式系统（DS）领域引入最小化的智能体相关概念，能够通过结合DS工程的既有技术与成熟的智能体理论，改进现代MAS的工程实践。本研究通过梳理MAS与DS的共同起源，建立架构层面的类比以形成统一的工程方法。随后，我们定义了最小化的智能体概念集，并开展两项实践研究来探索MAS开发的应用。首先，我们将这些概念融入DS架构模式中，设计了一个分布式MAS；其次，在研究生课程中运用这些概念，向无智能体理论背景的学生教授MAS工程知识。两门课程的学习成果均包括：学生能成功运用DS工具与技术实现MAS。尽管超过三分之二的学生无分布式系统开发实践经验，但两门课程的平均成绩均高于80%，验证了本方法的有效性。最后，我们探讨了本研究如何支持在遵循现有智能体相关研究成果的前提下，利用DS成熟技术与概念，协同现代AI技术开发先进系统。