The essence of autonomics is to manage business, system, and technical complexity. This requires new developments that enable components and systems to adapt to changing user needs, environmental conditions, and business goals. Adaptation requires context-aware, intelligent decision-making that orchestrates behavior. Supporting technologies include machine learning and reasoning, control theory, information and data modeling, ontology modeling, and semantic reasoning.
EDUCATION AND RESEARCH
We live in a networked world. Autonomics can be applied to both network communications and to nano- and bio-sensors and systems. Autonomic courseware includes an Introduction to Autonomics, which relates important software engineering courses to the goals of autonomics, as well as specialized courses in modeling, knowledge representation, and semantic reasoning. These courses provide a solid foundation for integrating elements from other IT convergence engineering courses to provide the student with the theory required to build new U-Health and U-Environment applications. Education focuses on knowledge representation and reasoning, dynamic code generation, and analysis using heterogeneous data from nano- and bio-sensors. Research is focused on using education to provide new ways to make intelligent decisions based on changing context, as well as enabling systems to learn from experience.