References

Kahn, M. (2021). Dynamic-Occlusion-Aware Risk Identification for Autonomous Vehicles Using Hypergames Retrieved from http://hdl.handle.net/10012/17774 (Original work published 2021)

Abdelzad, V., Lee, J., Sedwards, S., Soltani, S., & Czarnecki, K. (2021). Non-divergent Imitation for Verification of Complex Learned Controllers Shenzhen, China (virtual): IEEE. https://doi.org/10.1109/IJCNN52387.2021.9533410

Ernst, G., Sedwards, S., Zhang, Z., & Hasuo, I. (2021). Falsification of Hybrid Systems Using Adaptive Probabilistic Search ACM Transactions on Modeling and Computer Simulation (TOMACS), 31, 1-22. https://doi.org/10.1145/3459605

Lee, S., Lee, J., & Hasuo, I. (2021). Predictive PER: Balancing Priority and Diversity Towards Stable Deep Reinforcement Learning Shenzhen, China (virtual): IEEE. https://doi.org/10.1109/IJCNN52387.2021.9534243

Lee, J., & Sutton, R. S. (2021). Policy iterations for reinforcement learning problems in continuous time and space \textemdash Fundamental theory and methods Automatica, 126, 109421, 15 pages. https://doi.org/10.1016/j.automatica.2020.109421 (Original work published 2021)

Lee, J., Sedwards, S., & Czarnecki, K. (2021). Recursive Constraints to Prevent Instability in Constrained Reinforcement Learning Presented at the Recursive Constraints to Prevent Instability in Constrained Reinforcement Learning conference. Online at http://modem2021.cs.nuigalway.ie/. Retrieved from https://arxiv.org/abs/2201.07958

Salay, R., Czarnecki, K., Alvarez, I., Elli, M. S., Sedwards, S., & Weast, J. (2020). PURSS: Towards Perceptual Uncertainty Aware Responsibility Sensitive Safety with ML Presented at the PURSS: Towards Perceptual Uncertainty Aware Responsibility Sensitive Safety With ML conference. New York: CEUR.

Bouchard, F. (2020). Expert System and a Rule Set Development Method for Urban Behaviour Planning Retrieved from http://hdl.handle.net/10012/15864 (Original work published 2020)

Gaurav, A., Vernekar, S., Lee, J., Sedwards, S., Abdelzad, V., & Czarnecki, K. (2020). Simple Continual Learning Strategies for Safer Classifers Presented at the Simple Continual Learning Strategies for Safer Classifers conference. CEUR. Retrieved from http://ceur-ws.org/Vol-2560/paper6.pdf (Original work published 2020)

Budde, C., D’Argenio, P., Hartmanns, A., & Sedwards, S. (2020). An Efficient Statistical Model Checker for Nondeterminism and Rare Events International Journal on Software Tools For Technology Transfer, Special Issue TACAS 2018.