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
Reference author: Sean Sedwards
First name
Sean
Last name
Sedwards
Balakrishnan, A., Lee, J., Gaurav, A., Czarnecki, K., & Sedwards, S. (2021). Transfer Reinforcement Learning for Autonomous Driving: From WiseMove to WiseSim ACM Transactions on Modeling and Computer Simulation, 31, Article No. 15, pp 1~26. https://doi.org/10.1145/3449356 (Original work published 2021)
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.
Jhunjhunwala, A., Lee, J., Sedwards, S., Abdelzad, V., & Czarnecki, K. (2020). Improved Policy Extraction via Online Q-Value Distillation Presented at the Improved Policy Extraction via Online Q-Value Distillation conference. Glasgow: IEEE.
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.
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)
Babaee, R., Ganesh, V., & Sedwards, S. (2019). Accelerated Learning of Predictive Runtime Monitors for Rare Failure Porto, Portugal: Springer.
Ilievski, M., Sedwards, S., Gaurav, A., Balakrishnan, A., Sarkar, A., Lee, J., … Czarnecki, K. (2019). Design Space of Behaviour Planning for Autonomous Driving Waterloo. Retrieved from https://arxiv.org/abs/1908.07931 (Original work published 2019)
Ernst, G., Sedwards, S., Zhang, Z., & Hasuo, I. (2019). Fast Falsification of Hybrid Systems using Probabilistically Adaptive Input Glasgow, Scotland: Springer.