Johns Hopkins University 3 credits Computer Science
This course offers a comprehensive introduction to autonomic and self-aware computing, focusing on the self-managing and self-awareness properties of autonomic systems, their architectures, AI/ML/LLM support, and the decision-making processes required to achieve resiliency through continual adaptation. Students will explore the vision of autonomic computing, how it differs from automated and autonomous systems, and the biological inspirations and self-awareness characteristics that define it. The curriculum covers autonomic system architectures including autonomic managers responsible for self-management, alongside AI driven adaptive technologies, negotiation mechanisms, and the traits that make a system truly self-aware. Applications of autonomic computing are examined across domains such as security, resiliency, and cloud computing. Throughout the course, students will complete hands on programming assignments and an ongoing project that adds autonomic capabilities to a virtual IoT device, industrial control system, or another system of their choice, applying the theories and concepts introduced in lecture. Weekly readings and discussions support the learning process, supplemented by biweekly assignments that explore selected topics in greater depth. Students will also be encouraged to submit their project outcomes to a conference for publication.
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