Jan Leike Research Associate https://jan.leike.name/ Jan is working on long-term technical problems of robust and beneficial artificial intelligence. Previously he was a PhD student With Marcus Hutter and wrote his dissertation on general reinforcement learning. Publications (5) Lamont, S., Aslanides, J., Leike, J., Hutter, M. (2017). Generalised Discount Functions applied to a Monte-Carlo AIμ Implementation. arXiv preprint arXiv:103.01358v1 Aslanides, J., Leike, J., Hutter, M. (2017). Universal Reinforcement Learning Algorithms: Survey and Experiments. arXiv:1705.10557v1 Leike, J. (2016). Exploration potential. arXiv preprint: arXiv:1609.04994. Leike, J., Lattimore, T., Orseau, L. & Hutter, M. (2016). Thompson sampling is asymptotically optimal in general environments. Proceedings of the Thirty-Second Uncertainty in Artificial Intelligence Conference. Leike, J., Taylor, J., Fallenstein, B. (2016). A formal solution to the grain of truth problem. Proceedings of the Thirty-Second Uncertainty in Artificial Intelligence Conference.