AAAI 2023technical7 citations
Safety Validation of Learning-Based Autonomous Systems: A Multi-Fidelity Approach
Abstract
In recent years, learning-based autonomous systems have emerged as a promising tool for automating many crucial tasks. The key question is how we can build trust in such systems for safety-critical applications. My research aims to focus on the creation and validation of safety frameworks that leverage multiple sources of information. The ultimate goal is to establish a solid foundation for a long-term research program aimed at understanding the role of fidelity in simulators for safety validation and robot learning.
BibTeX
@article{Baheri_2024, title={Safety Validation of Learning-Based Autonomous Systems: A Multi-Fidelity Approach}, volume={37}, url={https://ojs.aaai.org/index.php/AAAI/article/view/26799}, DOI={10.1609/aaai.v37i13.26799}, abstractNote={In recent years, learning-based autonomous systems have emerged as a promising tool for automating many crucial tasks. The key question is how we can build trust in such systems for safety-critical applications. My research aims to focus on the creation and validation of safety frameworks that leverage multiple sources of information. The ultimate goal is to establish a solid foundation for a long-term research program aimed at understanding the role of fidelity in simulators for safety validation and robot learning.}, number={13}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Baheri, Ali}, year={2024}, month={Jul.}, pages={15432-15432} }