Tim Rudner one of 4 winners of the Qualcomm Innovation Fellowship (Europe)

Tim has been selected for his proposal: 'A Fully Probabilistic Theory of Autonomous Decision Making'. Tim's proposal is about developing a fully probabilistic framework for reinforcement learning to provide reliable and mathematically rigorous uncertainty quantification. In contrast to previous approaches, he proposes to treat both the learning process as well as the model components, such an agent's policy, probabilistically. The approach will combine advances in probabilistic inference and modelling with probabilistic reinforcement learning. This will enable autonomous vehicles and machines to'know what they know' as well as what they don't know, and therefore to operate more safely and reliably.