150 citations · 205 across the 4 of their papers we have counts for
6 papers
Representation Matters: Improving Perception and Exploration for Robotics
Markus Wulfmeier, Arunkumar Byravan, Tim Hertweck +8
Projecting high-dimensional environment observations into lower-dimensional structured representations can considerably improve data-efficiency for reinforcement learning in domain…
Disentangled Cumulants Help Successor Representations Transfer to New Tasks
Christopher Grimm, Irina Higgins, Andre Barreto +5
Biological intelligence can learn to solve many diverse tasks in a data efficient manner by re-using basic knowledge and skills from one task to another. Furthermore, many of such…
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…
Meta-Learning by the Baldwin Effect
Chrisantha Thomas Fernando, Jakub Sygnowski, Simon Osindero +6
The scope of the Baldwin effect was recently called into question by two papers that closely examined the seminal work of Hinton and Nowlan. To this date there has been no demonstr…
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…
Grounded Language Learning in a Simulated 3D World
Karl Moritz Hermann, Felix Hill, Simon Green +11
We are increasingly surrounded by artificially intelligent technology that takes decisions and executes actions on our behalf. This creates a pressing need for general means to com…