EAI Endorsed Transactions on Self-Adaptive Systems

A large class of software-intensive systems, including those for industrial automation, consumer electronics, airplanes, automobiles, medical devices, and civic infrastructure, must interact with the physical world. More advanced systems, such as unmanned autonomous systems, don’t just interact but also perceive important structural and dynamic aspects of their operational environment. To become interactive, an autonomous system must be aware of its physical environment and whereabouts, as well as its current internal status. This ability helps software-intensive systems sense, draw inferences, and react by exhibiting self-adaptation. As software is used for more pervasive and critical applications, support for self-adaptation is increasingly seen as necessary in avoiding costly disruptions for repair, maintenance and evolution of systems. A common understanding about the process of self-adaptation is the ability of a system to autonomously monitor its behavior and eventually modify the same according to changes in the operational environment or in the system itself. A good example of self-adaptive systems can be addressed to contemporary robotics systems that rely on the most recent advances in automation and robotic technologies to promote autonomy and self-adaptation to robotized systems.

The paradigm of self-adaptive systems is closely related to AI, which makes the research and development of such systems extremely challenging and demanding new approaches that can efficiently tackle the problems of expressing autonomy requirements, designing and implementing self-adaptive features, and efficiently testing self-adaptive behavior.

• AI for wireless communications
• AI for signal processing
• AI for image processing
• AI for medical/biological analysis, visualization and diagnosis
• AI for robotics
• AI for audio, language and speech processing
• AI for big data mining and analysis
• AI for emotion analysis
• AI for self-piloting automobile
• Applications in neuroscience
• Computer imaging, vision and graphics
• Machine learning
• Deep learning
• Deep reinforcement learning
• Pattern recognition
• Automated reasoning and inference
• Natural language processing
• Knowledge and data engineering

Special Issues Editor: Jorge De-j. Lozoya-santos (University of Monterrey, Mexico)

Bashar Nuseibeh (The Open University, UK and Lero, the Irish Software Engineering Research Center, University of Limerick)

Christopher Rouff (Johns Hopkins Applied Physics Laboratory)

Danny Weyns (Linnaeus University)

Diana Spears (Swarmotics LLC, Laramie, Wyoming, USA)

Franco Zambonelli (UNIMORE, Italy)

Genaina Rodrigues (University of Brasilia)

Giacomo Cabri (UNIMORE, Italy)

Imrich Chlamtac (CREATE-NET Research Consortium, University of Trento, Italy)

James Windsor (ESTEC, European Space Agency, Netherlands)

Michael O'Neill (UCD, Ireland)

Mike Hinchey (Lero, the Irish Software Engineering Research Center, University of Limerick)

Richard Antony (University of Greenwich)

Simon Dobson (University of St Andrews)

Temporarily closed open access journal abstracted/indexed in DBLP, CrossRef, EBSCO Discovery Services, and WorldCat. It focuses on artificial intelligence including smart manufacturing, smart cities and smart medical services and more, with no publishing fees.