17-707 Responsible AI & AI Governance: Identifying and Mitigating Risks
6 units, Carnegie Mellon University
Description: An increasingly important requirement for software-based systems is the ability to adapt at run time to handle such things as resource variability, changing user needs, and system faults. In this graduate seminar we will examine past and current research into self-adaptation in software systems, including planning, control systems, programming language design for adaptation, software architecture, fault-tolerant computing, and machine learning. Text: There will be no text, but course notes and papers will be made available. Evaluation: Grading will be based on discussions and student presentations in class and a report covering a specific aspect of self-healing systems. Topics to be covered: ? The rationale for self-adaptation in software systems. ? Foundational concepts, including control theory, utility theory, fault tolerance. ? Adaptation research in selected areas including autonomic computing, cloud computing, automated planning, machine learning, architecture-based adaptation, multi-fidelity computation, biologically-inspired models of computation, graceful degradation, mixed initiative systems, self-securing systems, adaptation for cloud computing. ? Case studies of successful ystems that use self-adaptation.
Prerequisites: none listed
Offered: Spring 2027
Courseweave needs JavaScript to show sections, workloads and planning tools.