What is it about?
This study contributes to fundamental theory on the definition and classification of autonomous and comparable system classes such as automated, intelligent, adaptive, autonomic, and organic systems. Although each individual system class has been extensively researched in recent decades, there are research gaps particularly with regard to the distinction between system class concepts in terms of similarities, differences, and relationships. The outcome is a very heterogeneous perspective on the delimitation of system classes in the current state of the art, evidenced by differing viewpoints on their intersection, for example, as interchangeable, distinct, or complementary research approaches. Therefore, this study performs a systematic literature review based on more than 300 articles to investigate the intersection of the system classes, emphasizing their similarities, differences, and relationships from the current state of the art.
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Why is it important?
Our systematic review unifies scattered perspectives on autonomous, automated, intelligent, adaptive, autonomic, and organic system classes. By clearly mapping similarities, differences, overlaps, and relationships, we enable researchers to recognize research gaps in the intersection of system classes, advance cross-disciplinary studies, leverage synergies for innovation, and support possible future standardization efforts with quantitative insights and categorization models. Furthermore, a clear distinction and classification of system types helps engineers, developers, and general practitioners to communicate and label technical systems more accurately. This reduces ambiguity in product development and documentation and integrates concepts from multiple fields to design next-generation autonomous systems benefiting from cross-field advances. Furthermore, we contribute to improved communication between communities to avoid misunderstandings and improve collaboration. Overall, our study lays the groundwork for a more unified and actionable understanding of self-x system classes. This enhances both the conceptual and practical foundation for ongoing scientific and technical progress on autonomous systems.
Perspectives
From a personal perspective, this publication represents an attempt to bring order into a fragmented research landscape and to connect communities that often work in parallel on closely related ideas. It is satisfying to see how a systematic review can reveal underlying structures between concepts that initially appear contradictory, and to translate these insights into guidance that both theorists and practitioners can use. The hope is that this work will encourage more cross-disciplinary collaboration and support clearer discussions about what “autonomous” and “self-x” systems really mean in future projects.
Inga Miadowicz
Deutsches Zentrum für Luft- und Raumfahrt
Read the Original
This page is a summary of: A Systematic Literature Review on the Intersection of Self-X System Classes, ACM Computing Surveys, November 2025, ACM (Association for Computing Machinery),
DOI: 10.1145/3778859.
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