Artificial intelligence

Esnaashari, S., Bright, J., Francis, J., Hashem, Y., Straub, V., & Morgan, D. (2023). Approaches to the Algorithmic Allocation of Public Resources: A Cross-disciplinary Review. arXiv preprint arXiv:2310.06475. DOI: https://doi.org/10.48550/arXiv.2310.06475

arXiv:2308.16538

Morgan, D., Hashem, Y., Straub, V. J., & Bright, J. (2022, December 1). High-stakes team based public sector decision making and AI oversight. https://doi.org/10.31235/osf.io/arq3w

Wang, J., Lembono, T. S., Kim, S., Calinon, S., Vijayakumar, S., & Tonneau, S. (Accepted/In press). Learning to Guide Online Multi-Contact Receding Horizon Planning. In Proceedings of the 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Leslie, D., Burr, C., Aitken, M., Cowls, J., Katell, M., and Briggs, M. (2021). Artificial intelligence, human rights, democracy, and the rule of law: a primer. The Council of Europe.

Gupta, Prateek, Tegan Maharaj, Martin Weiss, Nasim Rahaman, Hannah Alsdurf, Abhinav Sharma, Nanor Minoyan et al. "COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing." arXiv preprint arXiv:2010.16004 (2020).

Gupta, Prateek, Maxime Gasse, Elias B. Khalil, M. Pawan Kumar, Andrea Lodi, and Yoshua Bengio. "Hybrid models for learning to branch" NeurIPS 2020.