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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.11921 |
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| _version_ | 1866908654706360320 |
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| author | Xing, Liudong Janet Lin |
| author_facet | Xing, Liudong Janet Lin |
| contents | This chapter presents perspectives for challenges and future development in building reliable AI systems, particularly, agentic AI systems. Several open research problems related to mitigating the risks of cascading failures are discussed. The chapter also sheds lights on research challenges and opportunities in aspects including dynamic environments, inconsistent task execution, unpredictable emergent behaviors, as well as resource-intensive reliability mechanisms. In addition, several research directions along the line of testing and evaluating reliability of agentic AI systems are also discussed. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_11921 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Looking Forward: Challenges and Opportunities in Agentic AI Reliability Xing, Liudong Janet Lin Artificial Intelligence Emerging Technologies Performance This chapter presents perspectives for challenges and future development in building reliable AI systems, particularly, agentic AI systems. Several open research problems related to mitigating the risks of cascading failures are discussed. The chapter also sheds lights on research challenges and opportunities in aspects including dynamic environments, inconsistent task execution, unpredictable emergent behaviors, as well as resource-intensive reliability mechanisms. In addition, several research directions along the line of testing and evaluating reliability of agentic AI systems are also discussed. |
| title | Looking Forward: Challenges and Opportunities in Agentic AI Reliability |
| topic | Artificial Intelligence Emerging Technologies Performance |
| url | https://arxiv.org/abs/2511.11921 |