Lee, J. ., Sedwards, S. ., & Czarnecki, K. . (2021). Recursive Constraints to Prevent Instability in Constrained Reinforcement Learning. Recursive Constraints to Prevent Instability in Constrained Reinforcement Learning. Presented at the. Online at http://modem2021.cs.nuigalway.ie/. Retrieved from https://arxiv.org/abs/2201.07958
Publications
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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)
Sarkar, A. ., & Czarnecki, K. . (2021). Solution Concepts in Hierarchical Games Under Bounded Rationality With Applications to Autonomous Driving.. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/16715
Dillen, N. ., Ilievski, M. ., Law, E. ., Nacke, L. E., Czarnecki, K. ., & Schneider, O. . (2020). Keep Calm and Ride Along: Passenger Comfort and Anxiety as Physiological Responses to Autonomous Driving Styles. Keep Calm and Ride Along: Passenger Comfort and Anxiety As Physiological Responses to Autonomous Driving Styles. Presented at the. ACM. https://doi.org/10.1145/3313831.3376247 (Original work published 2020)
Chen, H. . (2020). Autonomous Vehicles with Visual Signals for Pedestrians: Experiments and Design Recommendations. Waterloo. Retrieved from https://uwspace.uwaterloo.ca/handle/10012/15534 (Original work published 2020)
Vernekar, S. . (2020). Training Reject-Classifiers for Out-of-distribution Detection via Explicit Boundary Sample Generation. Waterloo. Retrieved from http://hdl.handle.net/10012/15582 (Original work published 2020)
Antkiewicz, M. ., Kahn, M. ., Ala, M. ., Czarnecki, K. ., Wells, P. ., Acharya, A. ., & Beiker, S. . (2020). Modes of Automated Driving System Scenario Testing: Experience Report and Recommendations. SAE Int. J. Adv. & Curr. Prac. In Mobility, 2, 2248-2266. https://doi.org/10.4271/2020-01-1204 (Original work published 2020)
Balakrishnan, A. . (2020). Closing the Modelling Gap: Transfer Learning from a Low-Fidelity Simulator for Autonomous Driving. Waterloo. Retrieved from https://uwspace.uwaterloo.ca/handle/10012/15570 (Original work published 2020)
Valov, P. . (2020). Transferring Pareto Frontiers across Heterogeneous Hardware Environments. Waterloo. Retrieved from http://hdl.handle.net/10012/16295 (Original work published 2020)
Lee, S. ., Lee, J. ., & Hasuo, I. . (2020). Predictive PER: Balancing Priority and Diversity towards Stable Deep Reinforcement Learning. Predictive PER: Balancing Priority and Diversity towards Stable Deep Reinforcement Learning. Presented at the. Retrieved from https://sites.google.com/view/deep-rl-workshop-neurips2020/home