Przemysław Mazur — accepted AI-conference papers

2020

Urban Driving with Conditional Imitation Learning

Jeffrey Hawke, Richard Shen, Corina Gurau, Siddharth Sharma, Daniele Reda, Nikolay Nikolov +5

ICRA 2020poster

Hand-crafting generalised decision-making rules for real-world urban autonomous driving is hard. Alternatively, learning behaviour from easy-to-collect human driving demonstrations is appealing. Prior work has studied imitation learning (IL) for autonomous driving with a number of limitations. Examp…

Cited by 198 Source ↗Scholar ↗

2019

Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning

David Janz, Jiri Hron, Przemysław Mazur, Katja Hofmann, José Miguel Hernández-Lobato, Sebastian Tschiatschek

NeurIPS 2019poster

Posterior sampling for reinforcement learning (PSRL) is an effective method for balancing exploration and exploitation in reinforcement learning. Randomised value functions (RVF) can be viewed as a promising approach to scaling PSRL. However, we show that most contemporary algorithms combining RVF w…

Cited by 76 Source ↗PDF ↗Scholar ↗