Reference author: Sean Sedwards

D’Argenio, P. ., Gerhold, M. ., Hartmanns, A. ., & Sedwards, S. . (2018). A Hierarchy of Scheduler Classes for Stochastic Automata. Thessaloniki, Greece: Springer. Retrieved from https://link.springer.com/chapter/10.1007/978-3-319-89366-2_21

D’Argenio, P. ., Hartmanns, A. ., & Sedwards, S. . (2018). Lightweight Statistical Model Checking in Nondeterministic Continuous Time. Limassol, Cyprus: Springer. Retrieved from https://link.springer.com/chapter/10.1007/978-3-030-03421-4_22

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

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

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. Improved Policy Extraction via Online Q-Value Distillation. Presented at the. 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. PURSS: Towards Perceptual Uncertainty Aware Responsibility Sensitive Safety With ML. Presented at the. New York: CEUR.

Gaurav, A. ., Vernekar, S. ., Lee, J. ., Sedwards, S. ., Abdelzad, V. ., & Czarnecki, K. . (2020). Simple Continual Learning Strategies for Safer Classifers. Simple Continual Learning Strategies for Safer Classifers. Presented at the. 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.