原文传递
Assurance for Learning-Enabled Systems (ALES).
| 题名： | Assurance for Learning-Enabled Systems (ALES). |
| 作者： | Jha, S. |
| 摘要： | The Assurance for Learning-Enabled Systems project develops an integrated well-founded approach to the co-design ofcyberphyical systems with learning-enabled components and their assurance arguments for both perception and control. Theapproach was based on a theory of mind-predictive processing (PP) complemented with the dual process theories of reasoning.The research developed a two-layered runtime monitor using generative modeling in the first layer and graph Markov neuralnetworks based neurosymbolic contextual modeling in the second layer. |
| 总页数： | 56 pages |
相关文献
- Leveraging Symbolic Representations for Safe and Assured Learning.
- Formal Methods of Assurance for CPS.
- Advancing Cyber Assurance with Deep Learning.
- Background to New Entrant Safety Fitness Assurance Process
- Workshop on Assurance for Autonomous Systems for Aviation
- Developing Concept Learning Capabilities in the COGNET/IGEN Integrative architecture and Associated Agent-based Modeling and Behavioral Representation (AMBR) Air Traffic Control
检索历史
应用推荐
