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Resilience and Resilient Systems of Artificial Intelligence: Taxonomy, Models and Methods

A study on the resilience of artificial intelligence systems, including a taxonomy and analysis of relevant scientific publications.

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Resilience and Resilient Systems of Artificial Intelligence: Taxonomy, Models and Methods

By Viacheslav Moskalenko, Vyacheslav Kharchenko, Alona Moskalenko, Borys KuzikovAlgorithms
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The paper presents a systematic approach to analyzing AI system resilience, identifying sources of threats, and methods for ensuring resilience properties. It confirms the potential to create resilient AI systems by configuring architecture and learning scenarios.

The study provides a roadmap for establishing technical requirements and assessing existing AI system resilience.

Abstract

The paper presents a systematic approach to analyzing AI system resilience, identifying sources of threats, and methods for ensuring resilience properties. It confirms the potential to create resilient AI systems by configuring architecture and learning scenarios. The study provides a roadmap for establishing technical requirements and assessing existing AI system resilience.

A

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artificial intelligenceresiliencetaxonomymodelsmethodssystem analysisAI AgentsOntology & TaxonomySemantic InteroperabilityContent Operations
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