Evaluating Architectural Safeguards for Uncertain AI Black-Box Components
| dc.contributor.author | Scheerer, Max | |
| dc.date.accessioned | 2025-03-08T04:20:17Z | |
| dc.date.available | 2025-03-08T04:20:17Z | |
| dc.date.issued | 2023 | |
| dc.date.submitted | 2023-10-31T13:53:19Z | |
| dc.identifier | https://library.oapen.org/handle/20.500.12657/77095 | |
| dc.identifier.uri | https://doab-dev.siscern.org/handle/20.500.12854/178919 | |
| dc.description.abstract | Although tremendous progress has been made in Artificial Intelligence (AI), it entails new challenges. The growing complexity of learning tasks requires more complex AI components, which increasingly exhibit unreliable behaviour. In this book, we present a model-driven approach to model architectural safeguards for AI components and analyse their effect on the overall system reliability. | |
| dc.language | English | |
| dc.relation.ispartofseries | The Karlsruhe Series on Software Design and Quality | |
| dc.rights | open access | |
| dc.subject.classification | bic Book Industry Communication::P Mathematics & science | |
| dc.subject.other | self-adaptive systems; safeguarding AI; architectural reliability analysis; Software engineering; Selbst-Adaptive Systeme; Absicherung von KI; architekturelle Zuverlässigkeitsanalyse; Softwaretechnik | |
| dc.title | Evaluating Architectural Safeguards for Uncertain AI Black-Box Components | |
| dc.type | book | |
| oapen.identifier.doi | 10.5445/KSP/1000161585 | |
| oapen.relation.isPublishedBy | 68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2 | |
| oapen.pages | 472 | |
| dc.seriesnumber | 39 |
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