activity
20172024
most citedDistral: Robust Multitask Reinforcement Learning

182 citations · 798 across the 19 of their papers we have counts for

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Showing cs.AIShow all

5 papers · 1 filter

cs.AI2019

Attention-Privileged Reinforcement Learning

Sasha Salter, Dushyant Rao, Markus Wulfmeier +2

Image-based Reinforcement Learning is known to suffer from poor sample efficiency and generalisation to unseen visuals such as distractors (task-independent aspects of the observat…

cs.AI201949 cited

The StreetLearn Environment and Dataset

Piotr Mirowski, Andras Banki-Horvath, Keith Anderson +8

Navigation is a rich and well-grounded problem domain that drives progress in many different areas of research: perception, planning, memory, exploration, and optimisation in parti…

cs.AI2019

Learning To Follow Directions in Street View

Karl Moritz Hermann, Mateusz Malinowski, Piotr Mirowski +3

Navigating and understanding the real world remains a key challenge in machine learning and inspires a great variety of research in areas such as language grounding, planning, navi…

cs.AI2018

Learning to Navigate in Cities Without a Map

Piotr Mirowski, Matthew Koichi Grimes, Mateusz Malinowski +7

Navigating through unstructured environments is a basic capability of intelligent creatures, and thus is of fundamental interest in the study and development of artificial intellig…

cs.AI201753 cited

One-Shot Reinforcement Learning for Robot Navigation with Interactive Replay

Jake Bruce, Niko Suenderhauf, Piotr Mirowski +2

Recently, model-free reinforcement learning algorithms have been shown to solve challenging problems by learning from extensive interaction with the environment. A significant issu…