6 citations · 15 across the 3 of their papers we have counts for
3 papers
Uncertainty-sensitive Learning and Planning with Ensembles
Piotr Miłoś, Łukasz Kuciński, Konrad Czechowski +2
We propose a reinforcement learning framework for discrete environments in which an agent makes both strategic and tactical decisions. The former manifests itself through the use o…
Improved GQ-CNN: Deep Learning Model for Planning Robust Grasps
Maciej Jaśkowski, Jakub Świątkowski, Michał Zając +7
Recent developments in the field of robot grasping have shown great improvements in the grasp success rates when dealing with unknown objects. In this work we improve on one of the…
Atari games and Intel processors
Robert Adamski, Tomasz Grel, Maciej Klimek +1
The asynchronous nature of the state-of-the-art reinforcement learning algorithms such as the Asynchronous Advantage Actor-Critic algorithm, makes them exceptionally suitable for C…