Engineering Artificially Intelligent Systems
A Systems Engineering Approach to Realizing Synergistic Capabilities
James Llinas editor Ranjeev Mittu editor William F Lawless editor Donald A Sofge editor
Format:Paperback
Publisher:Springer Nature Switzerland AG
Published:17th Nov '21
Currently unavailable, and unfortunately no date known when it will be back
Many current AI and machine learning algorithms and data and information fusion processes attempt in software to estimate situations in our complex world of nested feedback loops. Such algorithms and processes must gracefully and efficiently adapt to technical challenges such as data quality induced by these loops, and interdependencies that vary in complexity, space, and time.
To realize effective and efficient designs of computational systems, a Systems Engineering perspective may provide a framework for identifying the interrelationships and patterns of change between components rather than static snapshots. We must study cascading interdependencies through this perspective to understand their behavior and to successfully adopt complex system-of-systems in society.
This book derives in part from the presentations given at the AAAI 2021 Spring Symposium session on Leveraging Systems Engineering to Realize Synergistic AI / Machine Learning Capabilities. Its 16 chapters offer an emphasis on pragmatic aspects and address topics in systems engineering; AI, machine learning, and reasoning; data and information fusion; intelligent systems; autonomous systems; interdependence and teamwork; human-computer interaction; trust; and resilience.
ISBN: 9783030893842
Dimensions: unknown
Weight: unknown
281 pages
1st ed. 2021